INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89815, 2019, 'plos', 'Large vessels as a tree of transmission lines incorporated in the CircAdapt whole-heart model: A computational tool to examine heart-vessel interaction', 'Heusinkveld, Maarten H G|Huberts, Wouter|Lumens, Joost|Arts, Theo|Delhaas, Tammo|Reesink, Koen D', 'Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands.|Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands.|Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands.|Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands.|Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands.|Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007173', '31306411', 'We developed a whole-circulation computational model by integrating a transmission line (TL) model describing vascular wave transmission into the established CircAdapt platform of whole-heart mechanics. In the present paper, we verify the numerical framework of our TL model by benchmark comparison to a previously validated pulse wave propagation (PWP) model. Additionally, we showcase the integrated CircAdapt-TL model, which now includes the heart as well as extensive arterial and venous trees with terminal impedances. We present CircAdapt-TL haemodynamics simulations of: 1) a systemic normotensive situation and 2) a systemic hypertensive situation. In the TL-PWP benchmark comparison we found good agreement regarding pressure and flow waveforms (relative errors xe2x89xa4 2.9% for pressure, and xe2x89xa4 5.6% for flow). CircAdapt-TL simulations reproduced the typically observed haemodynamic changes with hypertension, expressed by increases in mean and pulsatile blood pressures, and increased arterial pulse wave velocity. We observed a change in the timing of pressure augmentation (defined as a late-systolic boost in aortic pressure) from occurring after time of peak systolic pressure in the normotensive situation, to occurring prior to time of peak pressure in the hypertensive situation. The pressure augmentation could not be observed when the systemic circulation was lumped into a (non-linear) three-element windkessel model, instead of using our TL model. Wave intensity analysis at the carotid artery indicated earlier arrival of reflected waves with hypertension as compared to normotension, in good qualitative agreement with findings in patients. In conclusion, we successfully embedded a TL model as a vascular module into the CircAdapt platform. The integrated CircAdapt-TL model allows detailed studies on mechanistic studies on heart-vessel interaction.'),
(89816, 2019, 'plos', 'Computational design of improved standardized chemotherapy protocols for grade II oligodendrogliomas', 'Pérez-García, Víctor M|Ayala-Hernández, Luis E|Belmonte-Beitia, Juan|Schucht, Philippe|Murek, Michael|Raabe, Andreas|Sepúlveda, Juan', 'Department of Mathematics, Mathematical Oncology Laboratory (MOLAB), Universidad de Castilla-La Mancha, Avda. Camilo José Cela, 3, 13071 Ciudad Real, Spain.|Departamento de Ciencias Exactas y Tecnología Centro Universitario de los Lagos, Universidad de Guadalajara, Lagos de Moreno, Mexico.|Department of Mathematics, Mathematical Oncology Laboratory (MOLAB), Universidad de Castilla-La Mancha, Avda. Camilo José Cela, 3, 13071 Ciudad Real, Spain.|Universitätsklinik für Neurochirurgie, Bern University Hospital, CH-3010 Bern, Switzerland.|Universitätsklinik für Neurochirurgie, Bern University Hospital, CH-3010 Bern, Switzerland.|Universitätsklinik für Neurochirurgie, Bern University Hospital, CH-3010 Bern, Switzerland.|Oncology Unit, Hospital 12 de Octubre, Avda. de Córdoba s/n, 28041 Madrid, Spain.', 'Spain|Mexico|Spain|Switzerland|Switzerland|Switzerland|Spain', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1006778', '31306418', 'Here we put forward a mathematical model describing the response of low-grade (WHO grade II) oligodendrogliomas (LGO) to temozolomide (TMZ). The model describes the longitudinal volumetric dynamics of tumor response to TMZ of a cohort of 11 LGO patients treated with TMZ. After finding patient-specific parameters, different therapeutic strategies were tried computationally on the in-silico twins of those patients. Chemotherapy schedules with larger-than-standard rest periods between consecutive cycles had either the same or better long-term efficacy than the standard 28-day cycles. The results were confirmed in a large trial of 2000 virtual patients. These long-cycle schemes would also have reduced toxicity and defer the appearance of resistances. On the basis of those results, a combination scheme consisting of five induction TMZ cycles given monthly plus 12 maintenance cycles given every three months was found to provide substantial survival benefits for the in-silico twins of the 11 LGO patients (median 5.69 years, range: 0.67 to 68.45 years) and in a large virtual trial including 2000 patients. We used 220 sets of experiments in-silico to show that a clinical trial incorporating 100 patients per arm (standard intensive treatment versus 5 + 12 scheme) could demonstrate the superiority of the novel scheme after a follow-up period of 10 years. Thus, the proposed treatment plan could be the basis for a standardized TMZ treatment for LGO patients with survival benefits.'),
(89817, 2019, 'plos', 'Reservoir computing model of prefrontal cortex creates novel combinations of previous navigation sequences from hippocampal place-cell replay with spatial reward propagation', 'Cazin, Nicolas|Llofriu Alonso, Martin|Scleidorovich Chiodi, Pablo|Pelc, Tatiana|Harland, Bruce|Weitzenfeld, Alfredo|Fellous, Jean-Marc|Dominey, Peter Ford', 'INSERM, U1093, Cognition Action Plasticité Sensorimotrice, Université de Bourgogne, Dijon, France.|Department of Computer Science and Engineering, University of South Florida, Tampa, Florida, United States of America.|Department of Computer Science and Engineering, University of South Florida, Tampa, Florida, United States of America.|Department of Psychology, University of Arizona, Tucson, Arizona, United States of America.|Department of Psychology, University of Arizona, Tucson, Arizona, United States of America.|Department of Computer Science and Engineering, University of South Florida, Tampa, Florida, United States of America.|Department of Psychology, University of Arizona, Tucson, Arizona, United States of America.|INSERM, U1093, Cognition Action Plasticité Sensorimotrice, Université de Bourgogne, Dijon, France.', 'France|United States|United States|United States|United States|United States|United States|France', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006624', '31306421', 'As rats learn to search for multiple sources of food or water in a complex environment, they generate increasingly efficient trajectories between reward sites. Such spatial navigation capacity involves the replay of hippocampal place-cells during awake states, generating small sequences of spatially related place-cell activity that we call snippets. These snippets occur primarily during sharp-wave-ripples (SWRs). Here we focus on the role of such replay events, as the animal is learning a traveling salesperson task (TSP) across multiple trials. We hypothesize that snippet replay generates synthetic data that can substantially expand and restructure the experience available and make learning more optimal. We developed a model of snippet generation that is modulated by reward, propagated in the forward and reverse directions. This implements a form of spatial credit assignment for reinforcement learning. We use a biologically motivated computational framework known as reservoir computing to model prefrontal cortex (PFC) in sequence learning, in which large pools of prewired neural elements process information dynamically through reverberations. This PFC model consolidates snippets into larger spatial sequences that may be later recalled by subsets of the original sequences. Our simulation experiments provide neurophysiological explanations for two pertinent observations related to navigation. Reward modulation allows the system to reject non-optimal segments of experienced trajectories, and reverse replay allows the system to learn trajectories that it has not physically experienced, both of which significantly contribute to the TSP behavior.'),
(89818, 2019, 'plos', 'Morphophenotypic classification of tumor organoids as an indicator of drug exposure and penetration potential', 'Karolak, Aleksandra|Poonja, Sharan|Rejniak, Katarzyna A', 'Integrated Mathematical Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, United States of America.|Integrated Mathematical Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, United States of America.|Integrated Mathematical Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, United States of America.', 'United States|United States|United States', 5, '-', 'Journal Article', '10.1371/journal.pcbi.1007214', '31310602', 'The dynamics of tumor progression is driven by multiple factors, which can be exogenous to the tumor (microenvironment) or intrinsic (genetic, epigenetic or due to intercellular interactions). While tumor heterogeneity has been extensively studied on the level of cell genetic profiles or cellular composition, tumor morphological diversity has not been given as much attention. The limited analysis of tumor morphophenotypes may be attributed to the lack of accurate models, both experimental and computational, capable of capturing changes in tumor morphology with fine levels of spatial detail. Using a three-dimensional, agent-based, lattice-free computational model, we generated a library of multicellular tumor organoids, the experimental analogues of in vivo tumors. By varying three biologically relevant parameters-cell radius, cell division age and cell sensitivity to contact inhibition, we showed that tumor organoids with similar growth dynamics can express distinct morphologies and possess diverse cellular compositions. Taking advantage of the high-resolution of computational modeling, we applied the quantitative measures of compactness and accessible surface area, concepts that originated from the structural biology of proteins. Based on these analyses, we demonstrated that tumor organoids with similar sizes may differ in features associated with drug effectiveness, such as potential exposure to the drug or the extent of drug penetration. Both these characteristics might lead to major differences in tumor organoids response to therapy. This indicates that therapeutic protocols should not be based solely on tumor size, but take into account additional tumor features, such as their morphology or cellular packing density.'),
(89819, 2019, 'plos', 'Analyzing pharmacological intervention points: A method to calculate external stimuli to switch between steady states in regulatory networks', 'Breitenbach, Tim|Liang, Chunguang|Beyersdorf, Niklas|Dandekar, Thomas', 'Lehrstuhl für Bioinformatik, Biozentrum, Universität Würzburg, Würzburg, Germany.|Lehrstuhl für Bioinformatik, Biozentrum, Universität Würzburg, Würzburg, Germany.|Institut für Virologie und Immunbiologie, Universität Würzburg, Würzburg, Germany.|Lehrstuhl für Bioinformatik, Biozentrum, Universität Würzburg, Würzburg, Germany.', 'Germany|Germany|Germany|Germany', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007075', '31310618', 'Once biological systems are modeled by regulatory networks, the next step is to include external stimuli, which model the experimental possibilities to affect the activity level of certain networks nodes, in a mathematical framework. Then, this framework can be interpreted as a mathematical optimal control framework such that optimization algorithms can be used to determine external stimuli which cause a desired switch from an initial state of the network to another final state. These external stimuli are the intervention points for the corresponding biological experiment to obtain the desired outcome of the considered experiment. In this work, the model of regulatory networks is extended to controlled regulatory networks. For this purpose, external stimuli are considered which can affect the activity of the networks nodes by activation or inhibition. A method is presented how to calculate a selection of external stimuli which causes a switch between two different steady states of a regulatory network. A software solution based on Jimena and Mathworks Matlab is provided. Furthermore, numerical examples are presented to demonstrate application and scope of the software on networks of 4 nodes, 11 nodes and 36 nodes. Moreover, we analyze the aggregation of platelets and the behavior of a basic T-helper cell protein-protein interaction network and its maturation towards Th0, Th1, Th2, Th17 and Treg cells in accordance with experimental data.'),
(89820, 2019, 'plos', 'From skylight input to behavioural output: A computational model of the insect polarised light compass', 'Gkanias, Evripidis|Risse, Benjamin|Mangan, Michael|Webb, Barbara', 'School of Informatics, The University of Edinburgh, Edinburgh, United Kingdom.|Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany.|Department of Computer Science, University of Sheffield, Sheffield, United Kingdom.|School of Informatics, The University of Edinburgh, Edinburgh, United Kingdom.', 'United Kingdom|Germany|United Kingdom|United Kingdom', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1007123', '31318859', 'Many insects navigate by integrating the distances and directions travelled on an outward path, allowing direct return to the starting point. Fundamental to the reliability of this process is the use of a neural compass based on external celestial cues. Here we examine how such compass information could be reliably computed by the insect brain, given realistic constraints on the sky polarisation pattern and the insect eye sensor array. By processing the degree of polarisation in different directions for different parts of the sky, our model can directly estimate the solar azimuth and also infer the confidence of the estimate. We introduce a method to correct for tilting of the sensor array, as might be caused by travel over uneven terrain. We also show that the confidence can be used to approximate the change in sun position over time, allowing the compass to remain fixed with respect to true north during long excursions. We demonstrate that the compass is robust to disturbances and can be effectively used as input to an existing neural model of insect path integration. We discuss the plausibility of our model to be mapped to known neural circuits, and to be implemented for robot navigation.'),
(89821, 2019, 'plos', 'Assessing key decisions for transcriptomic data integration in biochemical networks', 'Richelle, Anne|Joshi, Chintan|Lewis, Nathan E', 'Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine, La Jolla, California, United States of America.|Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine, La Jolla, California, United States of America.|Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine, La Jolla, California, United States of America.', 'United States|United States|United States', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1007185', '31323017', 'To gain insights into complex biological processes, genome-scale data (e.g., RNA-Seq) are often overlaid on biochemical networks. However, many networks do not have a one-to-one relationship between genes and network edges, due to the existence of isozymes and protein complexes. Therefore, decisions must be made on how to overlay data onto networks. For example, for metabolic networks, these decisions include (1) how to integrate gene expression levels using gene-protein-reaction rules, (2) the approach used for selection of thresholds on expression data to consider the associated gene as active, and (3) the order in which these steps are imposed. However, the influence of these decisions has not been systematically tested. We compared 20 decision combinations using a transcriptomic dataset across 32 tissues and showed that definition of which reaction may be considered as active (i.e., reactions of the genome-scale metabolic network with a non-zero expression level after overlaying the data) is mainly influenced by thresholding approach used. To determine the most appropriate decisions, we evaluated how these decisions impact the acquisition of tissue-specific active reaction lists that recapitulate organ-system tissue groups. These results will provide guidelines to improve data analyses with biochemical networks and facilitate the construction of context-specific metabolic models.'),
(89822, 2019, 'plos', 'Assessment of the cardiovascular adverse effects of drug-drug interactions through a combined analysis of spontaneous reports and predicted drug-target interactions', 'Ivanov, Sergey|Lagunin, Alexey|Filimonov, Dmitry|Poroikov, Vladimir', 'Department of Bioinformatics, Institute of Biomedical Chemistry, Moscow, Russia.|Department of Bioinformatics, Institute of Biomedical Chemistry, Moscow, Russia.|Department of Bioinformatics, Institute of Biomedical Chemistry, Moscow, Russia.|Department of Bioinformatics, Institute of Biomedical Chemistry, Moscow, Russia.', '-|-|-|-', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1006851', '31323029', 'Adverse drug effects (ADEs) are one of the leading causes of death in developed countries and are the main reason for drug recalls from the market, whereas the ADEs that are associated with action on the cardiovascular system are the most dangerous and widespread. The treatment of human diseases often requires the intake of several drugs, which can lead to undesirable drug-drug interactions (DDIs), thus causing an increase in the frequency and severity of ADEs. An evaluation of DDI-induced ADEs is a nontrivial task and requires numerous experimental and clinical studies. Therefore, we developed a computational approach to assess the cardiovascular ADEs of DDIs. This approach is based on the combined analysis of spontaneous reports (SRs) and predicted drug-target interactions to estimate the five cardiovascular ADEs that are induced by DDIs, namely, myocardial infarction, ischemic stroke, ventricular tachycardia, cardiac failure, and arterial hypertension. We applied a method based on least absolute shrinkage and selection operator (LASSO) logistic regression to SRs for the identification of interacting pairs of drugs causing corresponding ADEs, as well as noninteracting pairs of drugs. As a result, five datasets containing, on average, 3100 potentially ADE-causing and non-ADE-causing drug pairs were created. The obtained data, along with information on the interaction of drugs with 1553 human targets predicted by PASS Targets software, were used to create five classification models using the Random Forest method. The average area under the ROC curve of the obtained models, sensitivity, specificity and balanced accuracy were 0.837, 0.764, 0.754 and 0.759, respectively. The predicted drug targets were also used to hypothesize the potential mechanisms of DDI-induced ventricular tachycardia for the top-scoring drug pairs. The created five classification models can be used for the identification of drug combinations that are potentially the most or least dangerous for the cardiovascular system.'),
(89823, 2019, 'plos', 'Propagation of orientation selectivity in a spiking network model of layered primary visual cortex', 'Merkt, Benjamin|Schüßler, Friedrich|Rotter, Stefan', 'Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany.|Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany.|Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany.', 'Germany|Germany|Germany', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007080', '31323031', 'Neurons in different layers of sensory cortex generally have different functional properties. But what determines firing rates and tuning properties of neurons in different layers? Orientation selectivity in primary visual cortex (V1) is an interesting case to study these questions. Thalamic projections essentially determine the preferred orientation of neurons that receive direct input. But how is this tuning propagated though layers, and how can selective responses emerge in layers that do not have direct access to the thalamus? Here we combine numerical simulations with mathematical analyses to address this problem. We find that a large-scale network, which just accounts for experimentally measured layer and cell-type specific connection probabilities, yields firing rates and orientation selectivities matching electrophysiological recordings in rodent V1 surprisingly well. Further analysis, however, is complicated by the fact that neuronal responses emerge in a dynamic fashion and cannot be directly inferred from static neuroanatomy, as some connections tend to have unintuitive effects due to recurrent interactions and strong feedback loops. These emergent phenomena can be understood by linearizing and coarse-graining. In fact, we were able to derive a low-dimensional linear dynamical system effectively describing stimulus-driven activity layer by layer. This low-dimensional system explains layer-specific firing rates and orientation tuning by accounting for the different gain factors of the aggregate system. Our theory can also be used to design novel optogenetic stimulation experiments, thus facilitating further exploration of the interplay between connectivity and function.'),
(89824, 2019, 'plos', 'Recombinant vector vaccine evolution', 'Bull, James J|Nuismer, Scott L|Antia, Rustom', 'Department Integrative Biology, University of Texas, Austin, Texas, United States of America.|Department of Biological Sciences, University of Idaho, Moscow, Idaho, United States of America.|Department of Biology, Emory University, Altanta, Georgia, United States of America.', 'United States|United States|Georgia', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1006857', '31323032', 'Replicating recombinant vector vaccines consist of a fully competent viral vector backbone engineered to express an antigen from a foreign transgene. From the perspective of viral replication, the transgene is not only dispensable but may even be detrimental. Thus vaccine revertants that delete or inactivate the transgene may evolve to dominate the vaccine virus population both during the process of manufacture of the vaccine as well as during the course of host infection. A particular concern is that this vaccine evolution could reduce its antigenicity-the immunity elicited to the transgene. We use mathematical and computational models to study vaccine evolution and immunity. These models include evolution arising during the process of manufacture, the dynamics of vaccine and revertant growth, plus innate and adaptive immunity elicited during the course of infection. Although the selective basis of vaccine evolution is easy to comprehend, the immunological consequences are not. One complication is that the opportunity for vaccine evolution is limited by the short period of within-host growth before the viral population is cleared. Even less obvious, revertant growth may only weakly interfere with vaccine growth in the host and thus have a limited effect on immunity to vaccine. Overall, we find that within-host vaccine evolution can sometimes compromise vaccine immunity, but only when the extent of evolution during vaccine manufacture is severe, and this evolution can be easily avoided or mitigated.'),
(89825, 2019, 'plos', 'Primacy coding facilitates effective odor discrimination when receptor sensitivities are tuned', 'Zwicker, David', 'Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.', 'Germany', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007188', '31323033', 'The olfactory system faces the difficult task of identifying an enormous variety of odors independent of their intensity. Primacy coding, where the odor identity is encoded by the receptor types that respond earliest, might provide a compact and informative representation that can be interpreted efficiently by the brain. In this paper, we analyze the information transmitted by a simple model of primacy coding using numerical simulations and statistical descriptions. We show that the encoded information depends strongly on the number of receptor types included in the primacy representation, but only weakly on the size of the receptor repertoire. The representation is independent of the odor intensity and the transmitted information is useful to perform typical olfactory tasks with close to experimentally measured performance. Interestingly, we find situations in which a smaller receptor repertoire is advantageous for discriminating odors. The model also suggests that overly sensitive receptor types could dominate the entire response and make the whole array useless, which allows us to predict how receptor arrays need to adapt to stay useful during environmental changes. Taken together, we show that primacy coding is more useful than simple binary and normalized coding, essentially because the sparsity of the odor representations is independent of the odor statistics, in contrast to the alternatives. Primacy coding thus provides an efficient odor representation that is independent of the odor intensity and might thus help to identify odors in the olfactory cortex.'),
(89826, 2019, 'plos', 'xcexb2-Methylamino-L-alanine substitution of serine in SOD1 suggests a direct role in ALS etiology', 'Proctor, Elizabeth A|Mowrey, David D|Dokholyan, Nikolay V', 'Departments of Neurosurgery, Pharmacology, and Biomedical Engineering, The Pennsylvania State University, Hershey, Pennsylvania, United States of America.|Department of Biochemistry & Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Departments of Pharmacology, Biochemistry & Molecular Biology, Chemistry, and Biomedical Engineering, The Pennsylvania State University, Hershey, Pennsylvania, United States of America.', 'United States|United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007225', '31323035', 'Exposure to the environmental toxin xcexb2-methylamino-L-alanine (BMAA) is linked to amyotrophic lateral sclerosis (ALS), but its disease-promoting mechanism remains unknown. We propose that incorporation of BMAA into the ALS-linked protein Cu,Zn superoxide dismutase (SOD1) upon translation promotes protein misfolding and aggregation, which has been linked to ALS onset and progression. Using molecular simulation and predictive energetic computation, we demonstrate that substituting any serine with BMAA in SOD1 results in structural destabilization and aberrant dynamics, promoting neurotoxic SOD1 aggregation. We propose that translational incorporation of BMAA into SOD1 is directly responsible for its toxicity in neurodegeneration, and BMAA modification of SOD1 may serve as a biomarker of ALS.'),
(89827, 2019, 'plos', 'Why do eukaryotic proteins contain more intrinsically disordered regions?', 'Basile, Walter|Salvatore, Marco|Bassot, Claudio|Elofsson, Arne', 'Science for Life Laboratory, Stockholm University, Solna, Sweden.|Science for Life Laboratory, Stockholm University, Solna, Sweden.|Science for Life Laboratory, Stockholm University, Solna, Sweden.|Science for Life Laboratory, Stockholm University, Solna, Sweden.', 'Sweden|Sweden|Sweden|Sweden', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007186', '31329574', 'Intrinsic disorder is more abundant in eukaryotic than prokaryotic proteins. Methods predicting intrinsic disorder are based on the amino acid sequence of a protein. Therefore, there must exist an underlying difference in the sequences between eukaryotic and prokaryotic proteins causing the (predicted) difference in intrinsic disorder. By comparing proteins, from complete eukaryotic and prokaryotic proteomes, we show that the difference in intrinsic disorder emerges from the linker regions connecting Pfam domains. Eukaryotic proteins have more extended linker regions, and in addition, the eukaryotic linkers are significantly more disordered, 38% vs. 12-16% disordered residues. Next, we examined the underlying reason for the increase in disorder in eukaryotic linkers, and we found that the changes in abundance of only three amino acids cause the increase. Eukaryotic proteins contain 8.6% serine, while prokaryotic proteins have 6.5%, eukaryotic proteins also contain 5.4% proline and 5.3% isoleucine compared with 4.0% proline and xe2x89x88 7.5% isoleucine in the prokaryotes. All these three differences contribute to the increased disorder in eukaryotic proteins. It is tempting to speculate that the increase in serine frequencies in eukaryotes is related to regulation by kinases, but direct evidence for this is lacking. The differences are observed in all phyla, protein families, structural regions and type of protein but are most pronounced in disordered and linker regions. The observation that differences in the abundance of three amino acids cause the difference in disorder between eukaryotic and prokaryotic proteins raises the question: Are amino acid frequencies different in eukaryotic linkers because the linkers are more disordered or do the differences cause the increased disorder?'),
(89828, 2019, 'plos', 'Ensemble of decision tree reveals potential miRNA-disease associations', 'Chen, Xing|Zhu, Chi-Chi|Yin, Jun', 'School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China.|School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China.|School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China.', 'China|China|China', 26, '-', 'Journal Article', '10.1371/journal.pcbi.1007209', '31329575', 'In recent years, increasing associations between microRNAs (miRNAs) and human diseases have been identified. Based on accumulating biological data, many computational models for potential miRNA-disease associations inference have been developed, which saves time and expenditure on experimental studies, making great contributions to researching molecular mechanism of human diseases and developing new drugs for disease treatment. In this paper, we proposed a novel computational method named Ensemble of Decision Tree based MiRNA-Disease Association prediction (EDTMDA), which innovatively built a computational framework integrating ensemble learning and dimensionality reduction. For each miRNA-disease pair, the feature vector was extracted by calculating the statistical measures, graph theoretical measures, and matrix factorization results for the miRNA and disease, respectively. Then multiple base learnings were built to yield many decision trees (DTs) based on random selection of negative samples and miRNA/disease features. Particularly, Principal Components Analysis was applied to each base learning to reduce feature dimensionality and hence remove the noise or redundancy. Average strategy was adopted for these DTs to get final association scores between miRNAs and diseases. In model performance evaluation, EDTMDA showed AUC of 0.9309 in global leave-one-out cross validation (LOOCV) and AUC of 0.8524 in local LOOCV. Additionally, AUC of 0.9192+/-0.0009 in 5-fold cross validation proved the models reliability and stability. Furthermore, three types of case studies for four human diseases were implemented. As a result, 94% (Esophageal Neoplasms), 86% (Kidney Neoplasms), 96% (Breast Neoplasms) and 88% (Carcinoma Hepatocellular) of top 50 predicted miRNAs were confirmed by experimental evidences in literature.'),
(89829, 2019, 'plos', 'Per-sample immunoglobulin germline inference from B cell receptor deep sequencing data', 'Ralph, Duncan K|Matsen, Frederick A', 'Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.', 'United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007133', '31329576', 'The collection of immunoglobulin genes in an individuals germline, which gives rise to B cell receptors via recombination, is known to vary significantly across individuals. In humans, for example, each individual has only a fraction of the several hundred known V alleles. Furthermore, the currently-accepted set of known V alleles is both incomplete (particularly for non-European samples), and contains a significant number of spurious alleles. The resulting uncertainty as to which immunoglobulin alleles are present in any given sample results in inaccurate B cell receptor sequence annotations, and in particular inaccurate inferred naive ancestors. In this paper we first show that the currently widespread practice of aligning each sequence to its closest match in the full set of IMGT alleles results in a very large number of spurious alleles that are not in the samples true set of germline V alleles. We then describe a new method for inferring each individuals germline gene set from deep sequencing data, and show that it improves upon existing methods by making a detailed comparison on a variety of simulated and real data samples. This new method has been integrated into the partis annotation and clonal family inference package, available at https://github.com/psathyrella/partis, and is run by default without affecting overall run time.'),
(89830, 2019, 'plos', 'Aberrant DNA methylation defines isoform usage in cancer, with functional implications', 'Chen, Yun-Ching|Elnitski, Laura', 'Genomic Functional Analysis Section, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America.|Genomic Functional Analysis Section, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007095', '31329578', 'Alternative transcript isoforms are common in tumors and act as potential drivers of cancer. Mechanisms determining altered isoform expression include somatic mutations in splice regulatory sites or altered splicing factors. However, since DNA methylation is known to regulate transcriptional isoform activity in normal cells, we predicted the highly dysregulated patterns of DNA methylation present in cancer also affect isoform activity. We analyzed DNA methylation and RNA-seq isoform data from 18 human cancer types and found frequent correlations specifically within 11 cancer types. Examining the top 25% of variable methylation sites revealed that the location of the methylated CpG site in a gene determined which isoform was used. In addition, the correlated methylation-isoform patterns classified tumors into known subtypes and predicted distinct protein functions between tumor subtypes. Finally, methylation-correlated isoforms were enriched for oncogenes, tumor suppressors, and cancer-related pathways. These findings provide new insights into the functional impact of dysregulated DNA methylation in cancer and highlight the relationship between the epigenome and transcriptome.'),
(89831, 2019, 'plos', 'Modeling human intuitions about liquid flow with particle-based simulation', 'Bates, Christopher J|Yildirim, Ilker|Tenenbaum, Joshua B|Battaglia, Peter', 'Department of Brain and Cognitive Sciences, Massachusetts Institue of Technology, Cambridge, Massachusetts, United States of America.|Department of Brain and Cognitive Sciences, Massachusetts Institue of Technology, Cambridge, Massachusetts, United States of America.|Department of Brain and Cognitive Sciences, Massachusetts Institue of Technology, Cambridge, Massachusetts, United States of America.|Department of Brain and Cognitive Sciences, Massachusetts Institue of Technology, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States', 4, '-', 'Journal Article', '10.1371/journal.pcbi.1007210', '31329579', 'Humans can easily describe, imagine, and, crucially, predict a wide variety of behaviors of liquids-splashing, squirting, gushing, sloshing, soaking, dripping, draining, trickling, pooling, and pouring-despite tremendous variability in their material and dynamical properties. Here we propose and test a computational model of how people perceive and predict these liquid dynamics, based on coarse approximate simulations of fluids as collections of interacting particles. Our model is analogous to a game engine in the head, drawing on techniques for interactive simulations (as in video games) that optimize for efficiency and natural appearance rather than physical accuracy. In two behavioral experiments, we found that the model accurately captured peoples predictions about how liquids flow among complex solid obstacles, and was significantly better than several alternatives based on simple heuristics and deep neural networks. Our model was also able to explain how peoples predictions varied as a function of the liquids properties (e.g., viscosity and stickiness). Together, the model and empirical results extend the recent proposal that human physical scene understanding for the dynamics of rigid, solid objects can be supported by approximate probabilistic simulation, to the more complex and unexplored domain of fluid dynamics.'),
(89832, 2019, 'plos', 'Biophysics and population size constrains speciation in an evolutionary model of developmental system drift', 'Khatri, Bhavin S|Goldstein, Richard A', 'The Francis Crick Institute, London, United Kingdom.|Division of Infection & Immunity, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007177', '31335870', 'Developmental system drift is a likely mechanism for the origin of hybrid incompatibilities between closely related species. We examine here the detailed mechanistic basis of hybrid incompatibilities between two allopatric lineages, for a genotype-phenotype map of developmental system drift under stabilising selection, where an organismal phenotype is conserved, but the underlying molecular phenotypes and genotype can drift. This leads to number of emergent phenomenon not obtainable by modelling genotype or phenotype alone. Our results show that: 1) speciation is more rapid at smaller population sizes with a characteristic, Orr-like, power law, but at large population sizes slow, characterised by a sub-diffusive growth law, 2) the molecular phenotypes under weakest selection contribute to the earliest incompatibilities, and 3) pair-wise incompatibilities dominate over higher order, contrary to previous predictions that the latter should dominate. The population size effect we find is consistent with previous results on allopatric divergence of transcription factor-DNA binding, where smaller populations have common ancestors with a larger drift load because genetic drift favours phenotypes which have a larger number of genotypes (higher sequence entropy) over more fit phenotypes which have far fewer genotypes, this means less substitutions are required in either lineage before incompatibilities arise. Overall, our results indicate that biophysics and population size provide a much stronger constraint to speciation than suggested by previous models, and point to a general mechanistic principle of how incompatibilities arise the under stabilising selection for an organismal phenotype.'),
(89833, 2019, 'plos', 'A case study in the functional consequences of scaling the sizes of realistic cortical models', 'Joglekar, Madhura R|Chariker, Logan|Shapley, Robert|Young, Lai-Sang', 'Courant Institute of Mathematical Sciences, New York, New York, United States of America.|Courant Institute of Mathematical Sciences, New York, New York, United States of America.|Center for Neural Science, New York University, New York, New York, United States of America.|Courant Institute of Mathematical Sciences, New York, New York, United States of America.', 'United States|United States|United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007198', '31335880', 'Neuroscience models come in a wide range of scales and specificity, from mean-field rate models to large-scale networks of spiking neurons. There are potential trade-offs between simplicity and realism, versatility and computational speed. This paper is about large-scale cortical network models, and the question we address is one of scalability: would scaling down cell density impact a networks ability to reproduce cortical dynamics and function? We investigated this problem using a previously constructed realistic model of the monkey visual cortex that is true to size. Reducing cell density gradually up to 50-fold, we studied changes in model behavior. Size reduction without parameter adjustment was catastrophic. Surprisingly, relatively minor compensation in synaptic weights guided by a theoretical algorithm restored mean firing rates and basic function such as orientation selectivity to models 10-20 times smaller than the real cortex. Not all was normal in the reduced model cortices: intracellular dynamics acquired a character different from that of real neurons, and while the ability to relay feedforward inputs remained intact, reduced models showed signs of deficiency in functions that required dynamical interaction among cortical neurons. These findings are not confined to models of the visual cortex, and modelers should be aware of potential issues that accompany size reduction. Broader implications of this study include the importance of homeostatic maintenance of firing rates, and the functional consequences of feedforward versus recurrent dynamics, ideas that may shed light on other species and on systems suffering cell loss.'),
(89834, 2019, 'plos', 'Mathematical model predicts anti-adhesion-antibiotic-debridement combination therapies can clear an antibiotic resistant infection', 'Roberts, Paul A|Huebinger, Ryan M|Keen, Emma|Krachler, Anne-Marie|Jabbari, Sara', 'School of Mathematics, University of Birmingham, Edgbaston, Birmingham, United Kingdom.|Department of Surgery, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.|Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, Edgbaston, Birmingham, United Kingdom.|Department of Microbiology and Molecular Genetics, University of Texas McGovern Medical School at Houston, Houston, Texas, United States of America.|School of Mathematics, University of Birmingham, Edgbaston, Birmingham, United Kingdom.', 'United Kingdom|United States|United Kingdom|United States|United Kingdom', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007211', '31335907', 'As antimicrobial resistance increases, it is crucial to develop new treatment strategies to counter the emerging threat. In this paper, we consider combination therapies involving conventional antibiotics and debridement, coupled with a novel anti-adhesion therapy, and their use in the treatment of antimicrobial resistant burn wound infections. Our models predict that anti-adhesion-antibiotic-debridement combination therapies can eliminate a bacterial infection in cases where each treatment in isolation would fail. Antibiotics are assumed to have a bactericidal mode of action, killing bacteria, while debridement involves physically cleaning a wound (e.g. with a cloth), removing free bacteria. Anti-adhesion therapy can take a number of forms. Here we consider adhesion inhibitors consisting of polystyrene microbeads chemically coupled to a protein known as multivalent adhesion molecule 7, an adhesin which mediates the initial stages of attachment of many bacterial species to host cells. Adhesion inhibitors competitively inhibit bacteria from binding to host cells, thus rendering them susceptible to removal through debridement. An ordinary differential equation model is developed and the antibiotic-related parameters are fitted against new in vitro data gathered for the present study. The model is used to predict treatment outcomes and to suggest optimal treatment strategies. Our model predicts that anti-adhesion and antibiotic therapies will combine synergistically, producing a combined effect which is often greater than the sum of their individual effects, and that anti-adhesion-antibiotic-debridement combination therapy will be more effective than any of the treatment strategies used in isolation. Further, the use of inhibitors significantly reduces the minimum dose of antibiotics required to eliminate an infection, reducing the chances that bacteria will develop increased resistance. Lastly, we use our model to suggest treatment regimens capable of eliminating bacterial infections within clinically relevant timescales.'),
(89835, 2019, 'plos', 'Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation', 'Seiler, Enrico|Trappe, Kathrin|Renard, Bernhard Y', 'Bioinformatics Unit (MF1), Department for Methods Development and Research Infrastructure, Robert Koch Institute, Berlin, Germany.|Bioinformatics Unit (MF1), Department for Methods Development and Research Infrastructure, Robert Koch Institute, Berlin, Germany.|Bioinformatics Unit (MF1), Department for Methods Development and Research Infrastructure, Robert Koch Institute, Berlin, Germany.', 'Germany|Germany|Germany', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007208', '31335917', 'Horizontal gene transfer (HGT) has changed the way we regard evolution. Instead of waiting for the next generation to establish new traits, especially bacteria are able to take a shortcut via HGT that enables them to pass on genes from one individual to another, even across species boundaries. The tool Daisy offers the first HGT detection approach based on read mapping that provides complementary evidence compared to existing methods. However, Daisy relies on the acceptor and donor organism involved in the HGT being known. We introduce DaisyGPS, a mapping-based pipeline that is able to identify acceptor and donor reference candidates of an HGT event based on sequencing reads. Acceptor and donor identification is akin to species identification in metagenomic samples based on sequencing reads, a problem addressed by metagenomic profiling tools. However, acceptor and donor references have certain properties such that these methods cannot be directly applied. DaisyGPS uses MicrobeGPS, a metagenomic profiling tool tailored towards estimating the genomic distance between organisms in the sample and the reference database. We enhance the underlying scoring system of MicrobeGPS to account for the sequence patterns in terms of mapping coverage of an acceptor and donor involved in an HGT event, and report a ranked list of reference candidates. These candidates can then be further evaluated by tools like Daisy to establish HGT regions. We successfully validated our approach on both simulated and real data, and show its benefits in an investigation of an outbreak involving Methicillin-resistant Staphylococcus aureus data.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89836, 2019, 'plos', 'Syntrophy emerges spontaneously in complex metabolic systems', 'Libby, Eric|Hébert-Dufresne, Laurent|Hosseini, Sayed-Rzgar|Wagner, Andreas', 'Integrated Science Lab, Umeå University, Umeå, Sweden.|Santa Fe Institute, Santa Fe, New Mexico, United States of America.|Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.|Santa Fe Institute, Santa Fe, New Mexico, United States of America.', 'Sweden|Mexico|Switzerland|Mexico', 6, '-', 'Journal Article', '10.1371/journal.pcbi.1007169', '31339876', 'Syntrophy allows a microbial community as a whole to survive in an environment, even though individual microbes cannot. The metabolic interdependence typical of syntrophy is thought to arise from the accumulation of degenerative mutations during the sustained co-evolution of initially self-sufficient organisms. An alternative and underexplored possibility is that syntrophy can emerge spontaneously in communities of organisms that did not co-evolve. Here, we study this de novo origin of syntrophy using experimentally validated computational techniques to predict an organisms viability from its metabolic reactions. We show that pairs of metabolisms that are randomly sampled from a large space of possible metabolism and viable on specific primary carbon sources often become viable on new carbon sources by exchanging metabolites. The same biochemical reactions that are required for viability on primary carbon sources also confer viability on novel carbon sources. Our observations highlight a new and important avenue for the emergence of metabolic adaptations and novel ecological interactions.'),
(89837, 2019, 'plos', 'Foraging as an evidence accumulation process', 'Davidson, Jacob D|El Hady, Ahmed', 'Department Collective Behavior, Max Planck Institute for Animal Behavior, Konstanz, Germany.|Princeton Neuroscience Institute, Princeton, New Jersey, United States of America.', 'Germany|Jersey', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007060', '31339878', 'The patch-leaving problem is a canonical foraging task, in which a forager must decide to leave a current resource in search for another. Theoretical work has derived optimal strategies for when to leave a patch, and experiments have tested for conditions where animals do or do not follow an optimal strategy. Nevertheless, models of patch-leaving decisions do not consider the imperfect and noisy sampling process through which an animal gathers information, and how this process is constrained by neurobiological mechanisms. In this theoretical study, we formulate an evidence accumulation model of patch-leaving decisions where the animal averages over noisy measurements to estimate the state of the current patch and the overall environment. We solve the model for conditions where foraging decisions are optimal and equivalent to the marginal value theorem, and perform simulations to analyze deviations from optimal when these conditions are not met. By adjusting the drift rate and decision threshold, the model can represent different strategies, for example an incremental, decremental, or counting strategy. These strategies yield identical decisions in the limiting case but differ in how patch residence times adapt when the foraging environment is uncertain. To describe sub-optimal decisions, we introduce an energy-dependent marginal utility function that predicts longer than optimal patch residence times when food is plentiful. Our model provides a quantitative connection between ecological models of foraging behavior and evidence accumulation models of decision making. Moreover, it provides a theoretical framework for potential experiments which seek to identify neural circuits underlying patch-leaving decisions.'),
(89838, 2019, 'plos', 'Predictions of time to HIV viral rebound following ART suspension that incorporate personal biomarkers', 'Conway, Jessica M|Perelson, Alan S|Li, Jonathan Z', 'Department of Mathematics and Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, Pennsylvania, United States of America.|Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Brigham and Womens Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.', 'United States|Mexico|United States', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007229', '31339888', 'Antiretroviral therapy (ART) effectively controls HIV infection, suppressing HIV viral loads. Suspension of therapy is followed by rebound of viral loads to high, pre-therapy levels. However, there is significant heterogeneity in speed of rebound, with some rebounds occurring within days, weeks, or sometimes years. We present a stochastic mathematical model to gain insight into these post-treatment dynamics, specifically characterizing the dynamics of short term viral rebounds (xe2x89xa4 60 days). Li et al. (2016) report that the size of the expressed HIV reservoir, i.e., cell-associated HIV RNA levels, and drug regimen correlate with the time between ART suspension and viral rebound to detectable levels. We incorporate this information and viral rebound times to parametrize our model. We then investigate insights offered by our model into the underlying dynamics of the latent reservoir. In particular, we refine previous estimates of viral recrudescence after ART interruption by accounting for heterogeneity in infection rebound dynamics, and determine a recrudescence rate of once every 2-4 days. Our parametrized model can be used to aid in design of clinical trials to study viral dynamics following analytic treatment interruption. We show how to derive informative personalized testing frequencies from our model and offer a proof-of-concept example. Our results represent first steps towards a model that can make predictions on a person living with HIV (PLWH)s rebound time distribution based on biomarkers, and help identify PLWH with long viral rebound delays.'),
(89839, 2019, 'plos', 'Ten simple rules for giving an effective academic job talk', 'Sura, Shayna A|Smith, Lauren L|Ambrose, Monique R|Amorim, C Eduardo Guerra|Beichman, Annabel C|Gomez, Ana C R|Juhn, Mark|Kandlikar, Gaurav S|Miller, Julie S|Mooney, Jazlyn|Mummah, Riley O|Lohmueller, Kirk E|Lloyd-Smith, James O', 'Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Human Genetics, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, '-', 'Editorial', '10.1371/journal.pcbi.1007163', '31344032', '-'),
(89840, 2019, 'plos', 'Ten simple rules for writing and sharing computational analyses in Jupyter Notebooks', 'Rule, Adam|Birmingham, Amanda|Zuniga, Cristal|Altintas, Ilkay|Huang, Shih-Cheng|Knight, Rob|Moshiri, Niema|Nguyen, Mai H|Rosenthal, Sara Brin|Pérez, Fernando|Rose, Peter W', 'Design Lab, UC San Diego, La Jolla, California, United States of America.|Center for Computational Biology and Bioinformatics, UC San Diego, La Jolla, California, United States of America.|Department of Pediatrics, UC San Diego, La Jolla, California, United States of America.|Data Science Hub, San Diego Supercomputer Center, UC San Diego, La Jolla, California, United States of America.|Data Science Hub, San Diego Supercomputer Center, UC San Diego, La Jolla, California, United States of America.|Department of Pediatrics, UC San Diego, La Jolla, California, United States of America.|Bioinformatics and Systems Biology Graduate Program, UC San Diego, La Jolla, California, United States of America.|Data Science Hub, San Diego Supercomputer Center, UC San Diego, La Jolla, California, United States of America.|Center for Computational Biology and Bioinformatics, UC San Diego, La Jolla, California, United States of America.|Department of Statistics and Berkeley Institute for Data Science, UC Berkeley, and Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Data Science Hub, San Diego Supercomputer Center, UC San Diego, La Jolla, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 7, '-', 'Editorial', '10.1371/journal.pcbi.1007007', '31344036', '-'),
(89841, 2019, 'plos', 'Heterogeneous susceptibility to rotavirus infection and gastroenteritis in two birth cohort studies: Parameter estimation and epidemiological implications', 'Lewnard, Joseph A|Lopman, Benjamin A|Parashar, Umesh D|Bennett, Aisleen|Bar-Zeev, Naor|Cunliffe, Nigel A|Samuel, Prasanna|Guerrero, M Lourdes|Ruiz-Palacios, Guillermo|Kang, Gagandeep|Pitzer, Virginia E', 'Division of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, Berkeley, California, United States of America.|Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.|Division of Viral Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.|Malawi-Liverpool-Wellcome Trust Clinical Research Programme, College of Medicine, University of Malawi, Blantyre, Malawi.|Malawi-Liverpool-Wellcome Trust Clinical Research Programme, College of Medicine, University of Malawi, Blantyre, Malawi.|Malawi-Liverpool-Wellcome Trust Clinical Research Programme, College of Medicine, University of Malawi, Blantyre, Malawi.|Department of Gastrointestinal Sciences, Christian Medical College, Vellore, Tamil Nadu, India.|Instituto Nacional de Ciences Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.|Instituto Nacional de Ciences Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.|Department of Gastrointestinal Sciences, Christian Medical College, Vellore, Tamil Nadu, India.|Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America.', 'United States|Georgia|Georgia|Malawi|Malawi|Malawi|India|Mexico|Mexico|India|United States', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007014', '31348775', 'Cohort studies, randomized trials, and post-licensure studies have reported reduced natural and vaccine-derived protection against rotavirus gastroenteritis (RVGE) in low- and middle-income countries. While susceptibility of children to rotavirus is known to vary within and between settings, implications for estimation of immune protection are not well understood. We sought to re-estimate naturally-acquired protection against rotavirus infection and RVGE, and to understand how differences in susceptibility among children impacted estimates. We re-analyzed data from studies conducted in Mexico City, Mexico and Vellore, India. Cumulatively, 573 rotavirus-unvaccinated children experienced 1418 rotavirus infections and 371 episodes of RVGE over 17,636 child-months. We developed a model that characterized susceptibility to rotavirus infection and RVGE among children, accounting for aspects of the natural history of rotavirus and differences in transmission rates between settings. We tested whether model-generated susceptibility measurements were associated with demographic and anthropometric factors, and with the severity of RVGE symptoms. We identified greater variation in susceptibility to rotavirus infection and RVGE in Vellore than in Mexico City. In both cohorts, susceptibility to rotavirus infection and RVGE were associated with male sex, lower birth weight, lower maternal education, and having fewer siblings, within Vellore, susceptibility was also associated with lower socioeconomic status. Children who were more susceptible to rotavirus also experienced higher rates of rotavirus-negative diarrhea, and higher risk of moderate-to-severe symptoms when experiencing RVGE. Simulations suggested that discrepant estimates of naturally-acquired immunity against RVGE can be attributed, in part, to between-setting differences in susceptibility of children, but result primarily from the interaction of transmission rates with age-dependent risk for infections to cause RVGE. We found that more children in Vellore than in Mexico City belong to a high-risk group for rotavirus infection and RVGE, and demonstrate that unmeasured individual- and age-dependent susceptibility may influence estimates of naturally-acquired immune protection against RVGE.'),
(89842, 2019, 'plos', 'The impact of DNA methylation on the cancer proteome', 'Magzoub, Majed Mohamed|Prunello, Marcos|Brennan, Kevin|Gevaert, Olivier', 'Biomedical Informatics Training Program, Department of Biomedical Data Science, Stanford University, Palo Alto, California, United States of America.|Department of Statistics, College of Pharmaceutical and Biochemical Sciences, National University of Rosario, Rosario, Argentina.|Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Palo Alto, California, United States of America.|Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Palo Alto, California, United States of America.', 'United States|Argentina|United States|United States', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1007245', '31356589', 'Aberrant DNA methylation disrupts normal gene expression in cancer and broadly contributes to oncogenesis. We previously developed MethylMix, a model-based algorithmic approach to identify epigenetically regulated driver genes. MethylMix identifies genes where methylation likely executes a functional role by using transcriptomic data to select only methylation events that can be linked to changes in gene expression. However, given that proteins more closely link genotype to phenotype recent high-throughput proteomic data provides an opportunity to more accurately identify functionally relevant abnormal methylation events. Here we present a MethylMix analysis that refines nominations for epigenetic driver genes by leveraging quantitative high-throughput proteomic data to select only genes where DNA methylation is predictive of protein abundance. Applying our algorithm across three cancer cohorts we find that using protein abundance data narrows candidate nominations, where the effect of DNA methylation is often buffered at the protein level. Next, we find that MethylMix genes predictive of protein abundance are enriched for biological processes involved in cancer including functions involved in epithelial and mesenchymal transition. Moreover, our results are also enriched for tumor markers which are predictive of clinical features like tumor stage and we find clustering using MethylMix genes predictive of protein abundance captures cancer subtypes.'),
(89843, 2019, 'plos', 'A model for the origin and development of visual orientation selectivity', 'Nguyen, Gratia|Freeman, Alan W', 'School of Medical Sciences, The University of Sydney, Camperdown, New South Wales, Australia.|School of Medical Sciences, The University of Sydney, Camperdown, New South Wales, Australia.', 'Australia|Australia', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007254', '31356590', 'Orientation selectivity is a key property of primary visual cortex that contributes, downstream, to object recognition. The origin of orientation selectivity, however, has been debated for decades. It is known that on- and off-centre subcortical pathways converge onto single neurons in primary visual cortex, and that the spatial offset between these pathways gives rise to orientation selectivity. On- and off-centre pathways are intermingled, however, so it is unclear how their inputs to cortex come to be spatially segregated. We here describe a model in which the segregation occurs through Hebbian strengthening and weakening of geniculocortical synapses during the development of the visual system. Our findings include the following. 1. Neighbouring on- and off-inputs to cortex largely cancelled each other at the start of development. At each receptive field location, the Hebbian process increased the strength of one input sign at the expense of the other sign, producing a spatial segregation of on- and off-inputs. 2. The resulting orientation selectivity was precise in that the bandwidths of the orientation tuning functions fell within empirical estimates. 3. The model produced maps of preferred orientation-complete with iso-orientation domains and pinwheels-similar to those found in real cortex. 4. These maps did not originate in cortical processes, but from clustering of off-centre subcortical pathways and the relative location of neighbouring on-centre clusters. We conclude that a model with intermingled on- and off-pathways shaped by Hebbian synaptic plasticity can explain both the origin and development of orientation selectivity.'),
(89844, 2019, 'plos', 'A computational framework for the morpho-elastic development of molluskan shells by surface and volume growth', 'Rudraraju, Shiva|Moulton, Derek E|Chirat, Régis|Goriely, Alain|Garikipati, Krishna', 'Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Mathematical Institute, University of Oxford, Oxford, United Kingdom.|UMR CNRS 5276 LGL-TPE, Université Lyon1, 69622 Villeurbanne Cedex, France.|Mathematical Institute, University of Oxford, Oxford, United Kingdom.|Departments of Mechanical Engineering and Mathematics, Michigan Institute for Computational Discovery & Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United Kingdom|France|United Kingdom|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007213', '31356591', 'Mollusk shells are an ideal model system for understanding the morpho-elastic basis of morphological evolution of invertebrates exoskeletons. During the formation of the shell, the mantle tissue secretes proteins and minerals that calcify to form a new incremental layer of the exoskeleton. Most of the existing literature on the morphology of mollusks is descriptive. The mathematical understanding of the underlying coupling between pre-existing shell morphology, de novo surface deposition and morpho-elastic volume growth is at a nascent stage, primarily limited to reduced geometric representations. Here, we propose a general, three-dimensional computational framework coupling pre-existing morphology, incremental surface growth by accretion, and morpho-elastic volume growth. We exercise this framework by applying it to explain the stepwise morphogenesis of seashells during growth: new material surfaces are laid down by accretive growth on the mantle whose form is determined by its morpho-elastic growth. Calcification of the newest surfaces extends the shell as well as creates a new scaffold that constrains the next growth step. We study the effects of surface and volumetric growth rates, and of previously deposited shell geometries on the resulting modes of mantle deformation, and therefore of the developing shells morphology. Connections are made to a range of complex shells ornamentations.'),
(89845, 2019, 'plos', 'Frontal cortex tracks surprise separately for different sensory modalities but engages a common inhibitory control mechanism', 'Wessel, Jan R|Huber, David E', 'Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, United States of America.|Department of Psychological and Brain Sciences, University of Massachusetts, Amherst, MA, United States of America.', 'United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006927', '31356593', 'The brain constantly generates predictions about the environment to guide action. Unexpected events lead to surprise and can necessitate the modification of ongoing behavior. Surprise can occur for any sensory domain, but it is not clear how these separate surprise signals are integrated to affect motor output. By applying a trial-to-trial Bayesian surprise model to human electroencephalography data recorded during a cross-modal oddball task, we tested whether there are separate predictive models for different sensory modalities (visual, auditory), or whether expectations are integrated across modalities such that surprise in one modality decreases surprise for a subsequent unexpected event in the other modality. We found that while surprise was represented in a common frontal signature across sensory modalities (the fronto-central P3 event-related potential), the single-trial amplitudes of this signature more closely conformed to a model with separate surprise terms for each sensory domain. We then investigated whether surprise-related fronto-central P3 activity indexes the rapid inhibitory control of ongoing behavior after surprise, as suggested by recent theories. Confirming this prediction, the fronto-central P3 amplitude after both auditory and visual unexpected events was highly correlated with the fronto-central P3 found after stop-signals (measured in a separate stop-signal task). Moreover, surprise-related and stopping-related activity loaded onto the same component in a cross-task independent components analysis. Together, these findings suggest that medial frontal cortex maintains separate predictive models for different sensory domains, but engages a common mechanism for inhibitory control of behavior regardless of the source of surprise.'),
(89846, 2019, 'plos', 'Depressive symptoms are associated with blunted reward learning in social contexts', 'Safra, Lou|Chevallier, Coralie|Palminteri, Stefano', 'Laboratoire de Neurosciences Cognitives et Computationnelles, Institut National de la Santé et de la Recherche Médicale, Paris, France.|Laboratoire de Neurosciences Cognitives et Computationnelles, Institut National de la Santé et de la Recherche Médicale, Paris, France.|Laboratoire de Neurosciences Cognitives et Computationnelles, Institut National de la Santé et de la Recherche Médicale, Paris, France.', 'France|France|France', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007224', '31356594', 'Depression is characterized by a marked decrease in social interactions and blunted sensitivity to rewards. Surprisingly, despite the importance of social deficits in depression, non-social aspects have been disproportionally investigated. As a consequence, the cognitive mechanisms underlying atypical decision-making in social contexts in depression are poorly understood. In the present study, we investigate whether deficits in reward processing interact with the social context and how this interaction is affected by self-reported depression and anxiety symptoms in the general population. Two cohorts of subjects (discovery and replication sample: N = 50 each) took part in an experiment involving reward learning in contexts with different levels of social information (absent, partial and complete). Behavioral analyses revealed a specific detrimental effect of depressive symptoms-but not anxiety-on behavioral performance in the presence of social information, i.e. when participants were informed about the choices of another player. Model-based analyses further characterized the computational nature of this deficit as a negative audience effect, rather than a deficit in the way others choices and rewards are integrated in decision making. To conclude, our results shed light on the cognitive and computational mechanisms underlying the interaction between social cognition, reward learning and decision-making in depressive disorders.'),
(89847, 2019, 'plos', 'Spatially constrained tumour growth affects the patterns of clonal selection and neutral drift in cancer genomic data', 'Chkhaidze, Ketevan|Heide, Timon|Werner, Benjamin|Williams, Marc J|Huang, Weini|Caravagna, Giulio|Graham, Trevor A|Sottoriva, Andrea', 'Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.|Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.|Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.|Evolution and Cancer Lab, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom.|Evolution and Cancer Lab, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom.|Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.|Evolution and Cancer Lab, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom.|Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007243', '31356595', 'Quantification of the effect of spatial tumour sampling on the patterns of mutations detected in next-generation sequencing data is largely lacking. Here we use a spatial stochastic cellular automaton model of tumour growth that accounts for somatic mutations, selection, drift and spatial constraints, to simulate multi-region sequencing data derived from spatial sampling of a neoplasm. We show that the spatial structure of a solid cancer has a major impact on the detection of clonal selection and genetic drift from both bulk and single-cell sequencing data. Our results indicate that spatial constrains can introduce significant sampling biases when performing multi-region bulk sampling and that such bias becomes a major confounding factor for the measurement of the evolutionary dynamics of human tumours. We also propose a statistical inference framework that incorporates spatial effects within a growing tumour and so represents a further step forwards in the inference of evolutionary dynamics from genomic data. Our analysis shows that measuring cancer evolution using next-generation sequencing while accounting for the numerous confounding factors remains challenging. However, mechanistic model-based approaches have the potential to capture the sources of noise and better interpret the data.'),
(89848, 2019, 'plos', 'Robustness of respiratory rhythm generation across dynamic regimes', 'Rubin, Jonathan E|Smith, Jeffrey C', 'Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Cellular and Systems Neurobiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006860', '31361738', 'A central issue in the study of the neural generation of respiratory rhythms is the role of the intrinsic pacemaking capabilities that some respiratory neurons exhibit. The debate on this issue has occurred in parallel to investigations of interactions among respiratory network neurons and how these contribute to respiratory behavior. In this computational study, we demonstrate how these two issues are inextricably linked. We use simulations and dynamical systems analysis to show that once a conditional respiratory pacemaker, which can be tuned across oscillatory and non-oscillatory dynamic regimes in isolation, is embedded into a respiratory network, its dynamics become masked: the network exhibits similar dynamical properties regardless of the conditional pacemaker nodes tuning, and that nodes outputs are dominated by network influences. Furthermore, the outputs of the respiratory central pattern generator as a whole are invariant to these changes of dynamical properties, which ensures flexible and robust performance over a wide dynamic range.'),
(89849, 2019, 'plos', 'Identifying important parameters in the inflammatory process with a mathematical model of immune cell influx and macrophage polarization', 'Torres, Marcella|Wang, Jing|Yannie, Paul J|Ghosh, Shobha|Segal, Rebecca A|Reynolds, Angela M', 'Department of Mathematics and Applied Mathematics, Virginia Commonwealth University, Richmond, Virginia, United States of America.|Department of Internal Medicine, Virginia Commonwealth University, Richmond, Virginia, United States of America.|Hunter Holmes McGuire VA Medical Center, Richmond, Virginia, United States of America.|Department of Internal Medicine, Virginia Commonwealth University, Richmond, Virginia, United States of America.|Department of Mathematics and Applied Mathematics, Virginia Commonwealth University, Richmond, Virginia, United States of America.|Department of Mathematics and Applied Mathematics, Virginia Commonwealth University, Richmond, Virginia, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007172', '31365522', 'In an inflammatory setting, macrophages can be polarized to an inflammatory M1 phenotype or to an anti-inflammatory M2 phenotype, as well as existing on a spectrum between these two extremes. Dysfunction of this phenotypic switch can result in a population imbalance that leads to chronic wounds or disease due to unresolved inflammation. Therapeutic interventions that target macrophages have therefore been proposed and implemented in diseases that feature chronic inflammation such as diabetes mellitus and atherosclerosis. We have developed a model for the sequential influx of immune cells in the peritoneal cavity in response to a bacterial stimulus that includes macrophage polarization, with the simplifying assumption that macrophages can be classified as M1 or M2. With this model, we were able to reproduce the expected timing of sequential influx of immune cells and mediators in a general inflammatory setting. We then fit this model to in vivo experimental data obtained from a mouse peritonitis model of inflammation, which is widely used to evaluate endogenous processes in response to an inflammatory stimulus. Model robustness is explored with local structural and practical identifiability of the proposed model a posteriori. Additionally, we perform sensitivity analysis that identifies the population of apoptotic neutrophils as a key driver of the inflammatory process. Finally, we simulate a selection of proposed therapies including points of intervention in the case of delayed neutrophil apoptosis, which our model predicts will result in a sustained inflammatory response. Our model can therefore provide hypothesis testing for therapeutic interventions that target macrophage phenotype and predict outcomes to be validated by subsequent experimentation.'),
(89850, 2019, 'plos', 'Efficiency of protein synthesis inhibition depends on tRNA and codon compositions', 'Rudorf, Sophia', 'Theory and Bio-Systems, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany.', 'Germany', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006979', '31369559', 'Regulation and maintenance of protein synthesis are vital to all organisms and are thus key targets of attack and defense at the cellular level. Here, we mathematically analyze protein synthesis for its sensitivity to the inhibition of elongation factor EF-Tu and/or ribosomes in dependence of the systems tRNA and codon compositions. We find that protein synthesis reacts ultrasensitively to a decrease in the elongation factors concentration for systems with an imbalance between codon usages and tRNA concentrations. For well-balanced tRNA/codon compositions, protein synthesis is impeded more effectively by the inhibition of ribosomes instead of EF-Tu. Our predictions are supported by re-evaluated experimental data as well as by independent computer simulations. Not only does the described ultrasensitivity render EF-Tu a distinguished target of protein synthesis inhibiting antibiotics. It may also enable persister cell formation mediated by toxin-antitoxin systems. The strong impact of the tRNA/codon composition provides a basis for tissue-specificities of disorders caused by mutations of human mitochondrial EF-Tu as well as for the potential use of EF-Tu targeting drugs for tissue-specific treatments.'),
(89851, 2019, 'plos', 'Bayesian hypothesis testing and experimental design for two-photon imaging data', 'Rogerson, Luke E|Zhao, Zhijian|Franke, Katrin|Euler, Thomas|Berens, Philipp', 'Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany.|Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany.|Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany.|Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany.|Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007205', '31374071', 'Variability, stochastic or otherwise, is a central feature of neural activity. Yet the means by which estimates of variation and uncertainty are derived from noisy observations of neural activity is often heuristic, with more weight given to numerical convenience than statistical rigour. For two-photon imaging data, composed of fundamentally probabilistic streams of photon detections, the problem is particularly acute. Here, we present a statistical pipeline for the inference and analysis of neural activity using Gaussian Process regression, applied to two-photon recordings of light-driven activity in ex vivo mouse retina. We demonstrate the flexibility and extensibility of these models, considering cases with non-stationary statistics, driven by complex parametric stimuli, in signal discrimination, hierarchical clustering and other inference tasks. Sparse approximation methods allow these models to be fitted rapidly, permitting them to actively guide the design of light stimulation in the midst of ongoing two-photon experiments.'),
(89852, 2019, 'plos', 'Every which way? On predicting tumor evolution using cancer progression models', 'Diaz-Uriarte, Ramon|Vasallo, Claudia', 'Department of Biochemistry, Universidad Autónoma de Madrid, Madrid, Spain.|Department of Biochemistry, Universidad Autónoma de Madrid, Madrid, Spain.', 'Spain|Spain', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007246', '31374072', 'Successful prediction of the likely paths of tumor progression is valuable for diagnostic, prognostic, and treatment purposes. Cancer progression models (CPMs) use cross-sectional samples to identify restrictions in the order of accumulation of driver mutations and thus CPMs encode the paths of tumor progression. Here we analyze the performance of four CPMs to examine whether they can be used to predict the true distribution of paths of tumor progression and to estimate evolutionary unpredictability. Employing simulations we show that if fitness landscapes are single peaked (have a single fitness maximum) there is good agreement between true and predicted distributions of paths of tumor progression when sample sizes are large, but performance is poor with the currently common much smaller sample sizes. Under multi-peaked fitness landscapes (i.e., those with multiple fitness maxima), performance is poor and improves only slightly with sample size. In all cases, detection regime (when tumors are sampled) is a key determinant of performance. Estimates of evolutionary unpredictability from the best performing CPM, among the four examined, tend to overestimate the true unpredictability and the bias is affected by detection regime, CPMs could be useful for estimating upper bounds to the true evolutionary unpredictability. Analysis of twenty-two cancer data sets shows low evolutionary unpredictability for several of the data sets. But most of the predictions of paths of tumor progression are very unreliable, and unreliability increases with the number of features analyzed. Our results indicate that CPMs could be valuable tools for predicting cancer progression but that, currently, obtaining useful predictions of paths of tumor progression from CPMs is dubious, and emphasize the need for methodological work that can account for the probably multi-peaked fitness landscapes in cancer.'),
(89853, 2019, 'plos', 'Reappraising the utility of Google Flu Trends', 'Kandula, Sasikiran|Shaman, Jeffrey', 'Department of Environmental Health Sciences, Columbia University, New York, New York, United States of America.|Department of Environmental Health Sciences, Columbia University, New York, New York, United States of America.', 'United States|United States', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1007258', '31374088', 'Estimation of influenza-like illness (ILI) using search trends activity was intended to supplement traditional surveillance systems, and was a motivation behind the development of Google Flu Trends (GFT). However, several studies have previously reported large errors in GFT estimates of ILI in the US. Following recent release of time-stamped surveillance data, which better reflects real-time operational scenarios, we reanalyzed GFT errors. Using three data sources-GFT: an archive of weekly ILI estimates from Google Flu Trends, ILIf: fully-observed ILI rates from ILINet, and, ILIp: ILI rates available in real-time based on partial reporting-five influenza seasons were analyzed and mean square errors (MSE) of GFT and ILIp as estimates of ILIf were computed. To correct GFT errors, a random forest regression model was built with ILI and GFT rates from the previous three weeks as predictors. An overall reduction in error of 44% was observed and the errors of the corrected GFT are lower than those of ILIp. An 80% reduction in error during 2012/13, when GFT had large errors, shows that extreme failures of GFT could have been avoided. Using autoregressive integrated moving average (ARIMA) models, one- to four-week ahead forecasts were generated with two separate data streams: ILIp alone, and with both ILIp and corrected GFT. At all forecast targets and seasons, and for all but two regions, inclusion of GFT lowered MSE. Results from two alternative error measures, mean absolute error and mean absolute proportional error, were largely consistent with results from MSE. Taken together these findings provide an error profile of GFT in the US, establish strong evidence for the adoption of search trends based nowcasts in influenza forecast systems, and encourage reevaluation of the utility of this data source in diverse domains.'),
(89854, 2019, 'plos', 'Energy-efficient information transfer at thalamocortical synapses', 'Harris, Julia Jade|Engl, Elisabeth|Attwell, David|Jolivet, Renaud Blaise', 'Department of Neuroscience, Physiology & Pharmacology, University College London, London, United Kingdom.|Department of Neuroscience, Physiology & Pharmacology, University College London, London, United Kingdom.|Department of Neuroscience, Physiology & Pharmacology, University College London, London, United Kingdom.|Department of Neuroscience, Physiology & Pharmacology, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007226', '31381555', 'We have previously shown that the physiological size of postsynaptic currents maximises energy efficiency rather than information transfer across the retinothalamic relay synapse. Here, we investigate information transmission and postsynaptic energy use at the next synapse along the visual pathway: from relay neurons in the thalamus to spiny stellate cells in layer 4 of the primary visual cortex (L4SS). Using both multicompartment Hodgkin-Huxley-type simulations and electrophysiological recordings in rodent brain slices, we find that increasing or decreasing the postsynaptic conductance of the set of thalamocortical inputs to one L4SS cell decreases the energy efficiency of information transmission from a single thalamocortical input. This result is obtained in the presence of random background input to the L4SS cell from excitatory and inhibitory corticocortical connections, which were simulated (both excitatory and inhibitory) or injected experimentally using dynamic-clamp (excitatory only). Thus, energy efficiency is not a unique property of strong relay synapses: even at the relatively weak thalamocortical synapse, each of which contributes minimally to the output firing of the L4SS cell, evolutionarily-selected postsynaptic properties appear to maximise the information transmitted per energy used.'),
(89855, 2019, 'plos', 'Motion, fixation probability and the choice of an evolutionary process', 'Herrerías-Azcué, Francisco|Pérez-Muñuzuri, Vicente|Galla, Tobias', 'Theoretical Physics, School of Physics and Astronomy, The University of Manchester, Manchester, United Kingdom.|Group of Nonlinear Physics, Faculty of Physics, University of Santiago de Compostela, Santiago de Compostela, Spain.|Theoretical Physics, School of Physics and Astronomy, The University of Manchester, Manchester, United Kingdom.', 'United Kingdom|Spain|United Kingdom', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007238', '31381556', 'Seemingly minor details of mathematical and computational models of evolution are known to change the effect of population structure on the outcome of evolutionary processes. For example, birth-death dynamics often result in amplification of selection, while death-birth processes have been associated with suppression. In many biological populations the interaction structure is not static. Instead, members of the population are in motion and can interact with different individuals at different times. In this work we study populations embedded in a flowing medium, the interaction network is then time dependent. We use computer simulations to investigate how this dynamic structure affects the success of invading mutants, and compare these effects for different coupled birth and death processes. Specifically, we show how the speed of the motion impacts the fixation probability of an invading mutant. Flows of different speeds interpolate between evolutionary dynamics on fixed heterogeneous graphs and well-stirred populations, this allows us to systematically compare against known results for static structured populations. We find that motion has an active role in amplifying or suppressing selection by fragmenting and reconnecting the interaction graph. While increasing flow speeds suppress selection for most evolutionary models, we identify characteristic responses to flow for the different update rules we test. In particular we find that selection can be maximally enhanced or suppressed at intermediate flow speeds.'),
(89856, 2019, 'plos', 'Colony entropy-Allocation of goods in ant colonies', 'Greenwald, Efrat|Eckmann, Jean-Pierre|Feinerman, Ofer', 'Department of Physics of Complex systems, Weizmann Institute of Science, Rehovot, Israel.|Département de Physique Théorique and Section de Mathématiques, University of Geneva, Geneva, Switzerland.|Department of Physics of Complex systems, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Switzerland|Israel', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1006925', '31381557', 'Allocation of goods is a key feature in defining the connection between the individual and the collective scale in any society. Both the process by which goods are to be distributed, and the resulting allocation to the members of the society may affect the success of the population as a whole. One of the most striking natural examples of a highly successful cooperative society is the ant colony which often acts as a single superorganism. In particular, each individual within the ant colony has a communal stomach which is used to store and share food with the other colony members by mouth to mouth feeding. Sharing food between communal stomachs allows the colony as a whole to get its food requirements and, more so, allows each individual within the colony to reach its nutritional intake target. The vast majority of colony members do not forage independently but obtain their food through secondary interactions in which food is exchanged between individuals. The global effect of this exchange is not well understood. To gain better understanding into this process we used fluorescence imaging to measure how food from a single external source is distributed and mixed within a Camponotus sanctus ant colony. Using entropic measures to quantify food-blending, we show that while collected food flows into all parts of the colony it mixes only partly. We show that mixing is controlled by the ants interaction rule which implies that only a fraction of the maximal potential is actually transferred. This rule leads to a robust blending process: i.e., neither the exact food volume that is transferred, nor the interaction schedule are essential to generate the global outcome. Finally, we show how the ants interaction rules may optimize a trade-off between fast dissemination and efficient mixing. Our results regarding the distribution of a single food source provide a baseline for future studies on distributed regulation of multiple food sources in social insect colonies.'),
(89857, 2019, 'plos', 'Reduced model to predict thrombin and fibrin during thrombosis on collagen/tissue factor under venous flow: Roles of xcexb3-fibrin and factor XIa', 'Chen, Jason|Diamond, Scott L', 'Department of Chemical and Biomolecular Engineering, Institute for Medicine and Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Chemical and Biomolecular Engineering, Institute for Medicine and Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|United States', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007266', '31381558', 'During thrombosis, thrombin generates fibrin, however fibrin reversibly binds thrombin with low affinity E-domain sites (KD = 2.8 xcexbcM) and high affinity xcexb3-fibrin sites (KD = 0.1 xcexbcM). For blood clotting on collagen/tissue factor (1 TF-molecule/xcexbcm2) at 200 s-1 wall shear rate, high xcexbcM-levels of intraclot thrombin suggest robust prothrombin penetration into clots. Setting intraclot zymogen concentrations to plasma levels (and neglecting cofactor rate limitations) allowed the linearization of 7 Michaelis-Menton reactions between 6 species to simulate intraclot generation of: Factors FXa (via TF/VIIa or FIXa), FIXa (via TF/FVIIa or FXIa), thrombin, fibrin, and FXIa. This reduced model [7 rates, 2 KDs, enzyme half-lives~1 min] predicted the measured clot elution rate of thrombin-antithrombin (TAT) and fragment F1.2 in the presence and absence of the fibrin inhibitor Gly-Pro-Arg-Pro. To predict intraclot fibrin reaching 30 mg/mL by 15 min, the model required fibrinogen penetration into the clot to be strongly diffusion-limited (actual rate/ideal rate = 0.05). The model required free thrombin in the clot (~100 nM) to have an elution half-life of ~2 sec, consistent with measured albumin elution, with most thrombin (>99%) being fibrin-bound. Thrombin-feedback activation of FXIa became prominent and reached 5 pM FXIa at >500 sec in the simulation, consistent with anti-FXIa experiments. In predicting intrathrombus thrombin and fibrin during 15-min microfluidic experiments, the model revealed cascade amplification from 30 pM levels of intrinsic tenase to 15 nM prothrombinase to 15 xcexbcM thrombin to 90 xcexbcM fibrin. Especially useful for multiscale simulation, this reduced model predicts thrombin and fibrin co-regulation during thrombosis under flow.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89858, 2019, 'plos', 'Predicting kinase inhibitors using bioactivity matrix derived informer sets', 'Zhang, Huikun|Ericksen, Spencer S|Lee, Ching-Pei|Ananiev, Gene E|Wlodarchak, Nathan|Yu, Peng|Mitchell, Julie C|Gitter, Anthony|Wright, Stephen J|Hoffmann, F Michael|Wildman, Scott A|Newton, Michael A', 'Department of Statistics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Small Molecule Screening Facility, Drug Development Core, UW-Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Department of Mathematics and Institute for Mathematical Science, National University of Singapore, Singapore.|Small Molecule Screening Facility, Drug Development Core, UW-Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Department of Statistics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennesse, United States of America.|Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Department of Computer Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Small Molecule Screening Facility, Drug Development Core, UW-Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Small Molecule Screening Facility, Drug Development Core, UW-Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Department of Statistics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.', 'United States|United States|Singapore|United States|United States|United States|United States|United', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1006813', '31381559', 'Prediction of compounds that are active against a desired biological target is a common step in drug discovery efforts. Virtual screening methods seek some active-enriched fraction of a library for experimental testing. Where data are too scarce to train supervised learning models for compound prioritization, initial screening must provide the necessary data. Commonly, such an initial library is selected on the basis of chemical diversity by some pseudo-random process (for example, the first few plates of a larger library) or by selecting an entire smaller library. These approaches may not produce a sufficient number or diversity of actives. An alternative approach is to select an informer set of screening compounds on the basis of chemogenomic information from previous testing of compounds against a large number of targets. We compare different ways of using chemogenomic data to choose a small informer set of compounds based on previously measured bioactivity data. We develop this Informer-Based-Ranking (IBR) approach using the Published Kinase Inhibitor Sets (PKIS) as the chemogenomic data to select the informer sets. We test the informer compounds on a target that is not part of the chemogenomic data, then predict the activity of the remaining compounds based on the experimental informer data and the chemogenomic data. Through new chemical screening experiments, we demonstrate the utility of IBR strategies in a prospective test on three kinase targets not included in the PKIS.'),
(89859, 2019, 'plos', 'Bayesian phylodynamics of avian influenza A virus H9N2 in Asia with time-dependent predictors of migration', 'Yang, Jing|Müller, Nicola F|Bouckaert, Remco|Xu, Bing|Drummond, Alexei J', 'College of Global Change and Earth System Science, Beijing Normal University, Beijing, China.|Department of Biosystems Science and Engineering, ETH Zürich, Zürich, Switzerland.|School of Computer Science, University of Auckland, Auckland, New Zealand.|College of Global Change and Earth System Science, Beijing Normal University, Beijing, China.|School of Computer Science, University of Auckland, Auckland, New Zealand.', 'China|Switzerland|New Zealand|China|New Zealand', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007189', '31386651', 'Model-based phylodynamic approaches recently employed generalized linear models (GLMs) to uncover potential predictors of viral spread. Very recently some of these models have allowed both the predictors and their coefficients to be time-dependent. However, these studies mainly focused on predictors that are assumed to be constant through time. Here we inferred the phylodynamics of avian influenza A virus H9N2 isolated in 12 Asian countries and regions under both discrete trait analysis (DTA) and structured coalescent (MASCOT) approaches. Using MASCOT we applied a new time-dependent GLM to uncover the underlying factors behind H9N2 spread. We curated a rich set of time-series predictors including annual international live poultry trade and national poultry production figures. This time-dependent phylodynamic prediction model was compared to commonly employed time-independent alternatives. Additionally the time-dependent MASCOT model allowed for the estimation of viral effective sub-population sizes and their changes through time, and these effective population dynamics within each country were predicted by a GLM. International annual poultry trade is a strongly supported predictor of virus migration rates. There was also strong support for geographic proximity as a predictor of migration rate in all GLMs investigated. In time-dependent MASCOT models, national poultry production was also identified as a predictor of virus genetic diversity through time and this signal was obvious in mainland China. Our application of a recently introduced time-dependent GLM predictors integrated rich time-series data in Bayesian phylodynamic prediction. We demonstrated the contribution of poultry trade and geographic proximity (potentially unheralded wild bird movements) to avian influenza spread in Asia. To gain a better understanding of the drivers of H9N2 spread, we suggest increased surveillance of the H9N2 virus in countries that are currently under-sampled as well as in wild bird populations in the most affected countries.'),
(89860, 2019, 'plos', 'Connecting signaling and metabolic pathways in EGF receptor-mediated oncogenesis of glioblastoma', 'Bag, Arup K|Mandloi, Sapan|Jarmalavicius, Saulius|Mondal, Susmita|Kumar, Krishna|Mandal, Chhabinath|Walden, Peter|Chakrabarti, Saikat|Mandal, Chitra', 'Cancer Biology and Inflammatory Disorder Division, Indian Institute of Chemical Biology, Kolkata, India.|Structural Biology and Bioinformatics Division, Indian Institute of Chemical Biology, Kolkata, India.|Department of Dermatology, Venerology and Allergology, Charité- Universitätsmedizin Berlin corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.|Cancer Biology and Inflammatory Disorder Division, Indian Institute of Chemical Biology, Kolkata, India.|Structural Biology and Bioinformatics Division, Indian Institute of Chemical Biology, Kolkata, India.|National Institute of Pharmaceutical Education and Research, Kolkata, India.|Department of Dermatology, Venerology and Allergology, Charité- Universitätsmedizin Berlin corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.|Structural Biology and Bioinformatics Division, Indian Institute of Chemical Biology, Kolkata, India.|Cancer Biology and Inflammatory Disorder Division, Indian Institute of Chemical Biology, Kolkata, India.', 'India|India|Germany|India|India|India|Germany|India|India', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007090', '31386654', 'As malignant transformation requires synchronization of growth-driving signaling (S) and metabolic (M) pathways, defining cancer-specific S-M interconnected networks (SMINs) could lead to better understanding of oncogenic processes. In a systems-biology approach, we developed a mathematical model for SMINs in mutated EGF receptor (EGFRvIII) compared to wild-type EGF receptor (EGFRwt) expressing glioblastoma multiforme (GBM). Starting with experimentally validated human protein-protein interactome data for S-M pathways, and incorporating proteomic data for EGFRvIII and EGFRwt GBM cells and patient transcriptomic data, we designed a dynamic model for EGFR-driven GBM-specific information flow. Key nodes and paths identified by in silico perturbation were validated experimentally when inhibition of signaling pathway proteins altered expression of metabolic proteins as predicted by the model. This demonstrated capacity of the model to identify unknown connections between signaling and metabolic pathways, explain the robustness of oncogenic SMINs, predict drug escape, and assist identification of drug targets and the development of combination therapies.'),
(89861, 2019, 'plos', 'On the optimal design of metabolic RNA labeling experiments', 'Uvarovskii, Alexey|Naarmann-de Vries, Isabel S|Dieterich, Christoph', 'Klaus Tschira Institute for Integrative Computational Cardiology and Department of Internal Medicine III, University Hospital Heidelberg, Heidelberg, Germany.|Department of Intensive Care Medicine, University Hospital Aachen, RWTH Aachen University, Aachen, Germany.|Klaus Tschira Institute for Integrative Computational Cardiology and Department of Internal Medicine III, University Hospital Heidelberg, Heidelberg, Germany.', 'Germany|Germany|Germany', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007252', '31390362', 'Massively parallel RNA sequencing (RNA-seq) in combination with metabolic labeling has become the de facto standard approach to study alterations in RNA transcription, processing or decay. Regardless of advances in the experimental protocols and techniques, every experimentalist needs to specify the key aspects of experimental design: For example, which protocol should be used (biochemical separation vs. nucleotide conversion) and what is the optimal labeling time? In this work, we provide approximate answers to these questions using the asymptotic theory of optimal design. Specifically, we investigate, how the variance of degradation rate estimates depends on the time and derive the optimal time for any given degradation rate. Subsequently, we show that an increase in sample numbers should be preferred over an increase in sequencing depth. Lastly, we provide some guidance on use cases when laborious biochemical separation outcompetes recent nucleotide conversion based methods (such as SLAMseq) and show, how inefficient conversion influences the precision of estimates. Code and documentation can be found at https://github.com/dieterich-lab/DesignMetabolicRNAlabeling.'),
(89862, 2019, 'plos', 'Directed migration shapes cooperation in spatial ecological public goods games', 'Funk, Felix|Hauert, Christoph', 'Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada.|Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada.', 'Canada|Canada', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006948', '31393867', 'From the microscopic to the macroscopic level, biological life exhibits directed migration in response to environmental conditions. Chemotaxis enables microbes to sense and move towards nutrient-rich regions or to avoid toxic ones. Socio-economic factors drive human populations from rural to urban areas. The effect of collective movement is especially significant when triggered in response to the generation of public goods. Microbial communities can, for instance, alter their environment through the secretion of extracellular substances. Some substances provide antibiotic-resistance, others provide access to nutrients or promote motility. However, in all cases the maintenance of public goods requires costly cooperation and is consequently susceptible to exploitation. The threat of exploitation becomes even more acute with motile individuals because defectors can avoid the consequences of their cheating. Here, we propose a model to investigate the effects of targeted migration and analyze the interplay between social conflicts and migration in ecological public goods. In particular, individuals can locate attractive regions by moving towards higher cooperator densities or avoid unattractive regions by moving away from defectors. Both migration patterns not only shape an individuals immediate environment but also affects the entire population. For example, defectors hunting cooperators have a homogenizing effect on population densities. This limits the production of the public good and hence inhibits the growth of the population. In contrast, aggregating cooperators promote the spontaneous formation of patterns through heterogeneous density distributions. The positive feedback between cooperator aggregation and public goods production, however, poses analytical and numerical challenges due to its tendency to develop discontinuous distributions. Thus, different modes of directed migration bear the potential to enhance or inhibit the emergence of complex and sometimes dynamic spatial arrangements. Interestingly, whenever patterns emerge, cooperation is promoted, on average, population densities rise, and the risk of extinction is reduced.'),
(89863, 2019, 'plos', 'Arrhythmia mechanisms and spontaneous calcium release: Bi-directional coupling between re-entrant and focal excitation', 'Colman, Michael A', 'School of Biomedical Sciences, University of Leeds, Leeds, United Kingdom.', 'United Kingdom', 4, '-', 'Journal Article', '10.1371/journal.pcbi.1007260', '31393876', 'Spontaneous sub-cellular calcium release events (SCRE) are conjectured to promote rapid arrhythmias associated with conditions such as heart failure and atrial fibrillation: they can underlie the emergence of spontaneous action potentials in single cells which can lead to arrhythmogenic triggers in tissue. The multi-scale mechanisms of the development of SCRE into arrhythmia triggers, and their dynamic interaction with the tissue substrate, remain elusive, rigorous and simultaneous study of dynamics from the nanometre to the centimetre scale is a major challenge. The aim of this study was to develop a computational approach to overcome this challenge and study potential bi-directional coupling between sub-cellular and tissue-scale arrhythmia phenomena. A framework comprising a hierarchy of computational models was developed, which includes detailed single-cell models describing spatio-temporal calcium dynamics in 3D, efficient non-spatial cell models, and both idealised and realistic tissue models. A phenomenological approach was implemented to reproduce SCRE morphology and variability in the efficient cell models, comprising the definition of analytical Spontaneous Release Functions (SRF) whose parameters may be randomly sampled from appropriate distributions in order to match either the 3D cell models or experimental data. Pro-arrhythmogenic pacing protocols were applied to initiate re-entry and promote calcium overload, leading to the emergence of SCRE. The SRF accurately reproduced the dynamics of SCRE and its dependence on environment variables under multiple different conditions. Sustained re-entrant excitation promoted calcium overload, and led to the emergence of focal excitations after termination. A purely functional mechanism of re-entry and focal activity localisation was demonstrated, related to the unexcited spiral wave core. In conclusion, a novel approach has been developed to dynamically model SCRE at the tissue scale, which facilitates novel, detailed multi-scale mechanistic analysis. It was revealed that complex re-entrant excitation patterns and SCRE may be bi-directionally coupled, promoting novel mechanisms of arrhythmia perpetuation.'),
(89864, 2019, 'plos', 'Predicting the effects of deep brain stimulation using a reduced coupled oscillator model', 'Weerasinghe, Gihan|Duchet, Benoit|Cagnan, Hayriye|Brown, Peter|Bick, Christian|Bogacz, Rafal', 'MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.|MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.|MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.|MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.|Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, Oxford, United Kingdom.|MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1006575', '31393880', 'Deep brain stimulation (DBS) is known to be an effective treatment for a variety of neurological disorders, including Parkinsons disease and essential tremor (ET). At present, it involves administering a train of pulses with constant frequency via electrodes implanted into the brain. New closed-loop approaches involve delivering stimulation according to the ongoing symptoms or brain activity and have the potential to provide improvements in terms of efficiency, efficacy and reduction of side effects. The success of closed-loop DBS depends on being able to devise a stimulation strategy that minimizes oscillations in neural activity associated with symptoms of motor disorders. A useful stepping stone towards this is to construct a mathematical model, which can describe how the brain oscillations should change when stimulation is applied at a particular state of the system. Our work focuses on the use of coupled oscillators to represent neurons in areas generating pathological oscillations. Using a reduced form of the Kuramoto model, we analyse how a patient should respond to stimulation when neural oscillations have a given phase and amplitude, provided a number of conditions are satisfied. For such patients, we predict that the best stimulation strategy should be phase specific but also that stimulation should have a greater effect if applied when the amplitude of brain oscillations is lower. We compare this surprising prediction with data obtained from ET patients. In light of our predictions, we also propose a new hybrid strategy which effectively combines two of the closed-loop strategies found in the literature, namely phase-locked and adaptive DBS.'),
(89865, 2019, 'plos', 'A generative learning model for saccade adaptation', 'Cassanello, Carlos R|Ostendorf, Florian|Rolfs, Martin', 'Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany.|Department of Neurology, Charité - University Medicine Berlin, Berlin, Germany.|Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany.', 'Germany|Germany|Germany', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1006695', '31398185', 'Plasticity in the oculomotor system ensures that saccadic eye movements reliably meet their visual goals-to bring regions of interest into foveal, high-acuity vision. Here, we present a comprehensive description of sensorimotor learning in saccades. We induced continuous adaptation of saccade amplitudes using a double-step paradigm, in which participants saccade to a peripheral target stimulus, which then undergoes a surreptitious, intra-saccadic shift (ISS) as the eyes are in flight. In our experiments, the ISS followed a systematic variation, increasing or decreasing from one saccade to the next as a sinusoidal function of the trial number. Over a large range of frequencies, we confirm that adaptation gain shows (1) a periodic response, reflecting the frequency of the ISS with a delay of a number of trials, and (2) a simultaneous drift towards lower saccade gains. We then show that state-space-based linear time-invariant systems (LTIS) represent suitable generative models for this evolution of saccade gain over time. This state-equation algorithm computes the prediction of an internal (or hidden state-) variable by learning from recent feedback errors, and it can be compared to experimentally observed adaptation gain. The algorithm also includes a forgetting rate that quantifies per-trial leaks in the adaptation gain, as well as a systematic, non-error-based bias. Finally, we study how the parameters of the generative models depend on features of the ISS. Driven by a sinusoidal disturbance, the state-equation admits an exact analytical solution that expresses the parameters of the phenomenological description as functions of those of the generative model. Together with statistical model selection criteria, we use these correspondences to characterize and refine the structure of compatible state-equation models. We discuss the relation of these findings to established results and suggest that they may guide further design of experimental research across domains of sensorimotor adaptation.'),
(89866, 2019, 'plos', 'Aggressive or moderate drug therapy for infectious diseases? Trade-offs between different treatment goals at the individual and population levels', 'Scire, Jérémie|Hozé, Nathanaël|Uecker, Hildegard', 'Institute of Integrative Biology, ETH Zürich, Zürich, Switzerland.|Institute of Integrative Biology, ETH Zürich, Zürich, Switzerland.|Institute of Integrative Biology, ETH Zürich, Zürich, Switzerland.', 'Switzerland|Switzerland|Switzerland', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007223', '31404059', 'Antimicrobial resistance is one of the major public health threats of the 21st century. There is a pressing need to adopt more efficient treatment strategies in order to prevent the emergence and spread of resistant strains. The common approach is to treat patients with high drug doses, both to clear the infection quickly and to reduce the risk of de novo resistance. Recently, several studies have argued that, at least in some cases, low-dose treatments could be more suitable to reduce the within-host emergence of antimicrobial resistance. However, the choice of a drug dose may have consequences at the population level, which has received little attention so far. Here, we study the influence of the drug dose on resistance and disease management at the host and population levels. We develop a nested two-strain model and unravel trade-offs in treatment benefits between an individual and the community. We use several measures to evaluate the benefits of any dose choice. Two measures focus on the emergence of resistance, at the host level and at the population level. The other two focus on the overall treatment success: the outbreak probability and the disease burden. We find that different measures can suggest different dosing strategies. In particular, we identify situations where low doses minimize the risk of emergence of resistance at the individual level, while high or intermediate doses prove most beneficial to improve the treatment efficiency or even to reduce the risk of resistance in the population.'),
(89867, 2019, 'plos', 'Machine learning-based microarray analyses indicate low-expression genes might collectively influence PAH disease', 'Cui, Song|Wu, Qiang|West, James|Bai, Jiangping', 'College of Agronomy, Gansu Agricultural University, Lanzhou, Gansu, China.|Department of Mathematics, Middle Tennessee State University, Murfreesboro, Tennessee, United States of America.|Department of Medicine, Pulmonary Vascular Research Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.|College of Agronomy, Gansu Agricultural University, Lanzhou, Gansu, China.', 'China|United States|United States|China', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007264', '31404060', 'Accurately predicting and testing the types of Pulmonary arterial hypertension (PAH) of each patient using cost-effective microarray-based expression data and machine learning algorithms could greatly help either identifying the most targeting medicine or adopting other therapeutic measures that could correct/restore defective genetic signaling at the early stage. Furthermore, the prediction model construction processes can also help identifying highly informative genes controlling PAH, leading to enhanced understanding of the disease etiology and molecular pathways. In this study, we used several different gene filtering methods based on microarray expression data obtained from a high-quality patient PAH dataset. Following that, we proposed a novel feature selection and refinement algorithm in conjunction with well-known machine learning methods to identify a small set of highly informative genes. Results indicated that clusters of small-expression genes could be extremely informative at predicting and differentiating different forms of PAH. Additionally, our proposed novel feature refinement algorithm could lead to significant enhancement in model performance. To summarize, integrated with state-of-the-art machine learning and novel feature refining algorithms, the most accurate models could provide near-perfect classification accuracies using very few (close to ten) low-expression genes.'),
(89868, 2019, 'plos', 'Pulse transit time estimation of aortic pulse wave velocity and blood pressure using machine learning and simulated training data', 'Huttunen, Janne M J|Kärkkäinen, Leo|Lindholm, Harri', 'Nokia Bell Laboratories, Espoo, Finland.|Nokia Bell Laboratories, Espoo, Finland.|Nokia Bell Laboratories, Espoo, Finland.', 'Finland|Finland|Finland', 6, '-', 'Journal Article', '10.1371/journal.pcbi.1007259', '31415554', 'Recent developments in cardiovascular modelling allow us to simulate blood flow in an entire human body. Such model can also be used to create databases of virtual subjects, with sizes limited only by computational resources. In this work, we study if it is possible to estimate cardiovascular health indices using machine learning approaches. In particular, we carry out theoretical assessment of estimating aortic pulse wave velocity, diastolic and systolic blood pressure and stroke volume using pulse transit/arrival timings derived from photopletyshmography signals. For predictions, we train Gaussian process regression using a database of virtual subjects generated with a cardiovascular simulator. Simulated results provides theoretical assessment of accuracy for predictions of the health indices. For instance, aortic pulse wave velocity can be estimated with a high accuracy (r > 0.9) when photopletyshmography is measured from left carotid artery using a combination of foot-to-foot pulse transmit time and peak location derived for the predictions. Similar accuracy can be reached for diastolic blood pressure, but predictions of systolic blood pressure are less accurate (r > 0.75) and the stroke volume predictions are mostly contributed by heart rate.'),
(89869, 2019, 'plos', 'Recombination and mutational robustness in neutral fitness landscapes', 'Klug, Alexander|Park, Su-Chan|Krug, Joachim', 'Institute for Biological Physics, University of Cologne, Cologne, Germany.|Department of Physics, The Catholic University of Korea, Bucheon, Republic of Korea.|Institute for Biological Physics, University of Cologne, Cologne, Germany.', 'Germany|-|Germany', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006884', '31415555', 'Mutational robustness quantifies the effect of random mutations on fitness. When mutational robustness is high, most mutations do not change fitness or have only a minor effect on it. From the point of view of fitness landscapes, robust genotypes form neutral networks of almost equal fitness. Using deterministic population models it has been shown that selection favors genotypes inside such networks, which results in increased mutational robustness. Here we demonstrate that this effect is massively enhanced by recombination. Our results are based on a detailed analysis of mesa-shaped fitness landscapes, where we derive precise expressions for the dependence of the robustness on the landscape parameters for recombining and non-recombining populations. In addition, we carry out numerical simulations on different types of random holey landscapes as well as on an empirical fitness landscape. We show that the mutational robustness of a genotype generally correlates with its recombination weight, a new measure that quantifies the likelihood for the genotype to arise from recombination. We argue that the favorable effect of recombination on mutational robustness is a highly universal feature that may have played an important role in the emergence and maintenance of mechanisms of genetic exchange.'),
(89870, 2019, 'plos', 'Size and structure of the sequence space of repeat proteins', 'Marchi, Jacopo|Galpern, Ezequiel A|Espada, Rocio|Ferreiro, Diego U|Walczak, Aleksandra M|Mora, Thierry', 'Laboratoire de physique de l\\xc3x89cole normale supxc3xa9rieure (PSL University), CNRS, Sorbonne Universitxc3xa9, and Universitxc3xa9 de Paris, 75005 Paris, France.|Protein Physiology Lab, Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Quxc3xadmica Biolxc3xb3gica, Buenos Aires, Argentina.|Laboratoire Gulliver, Ecole supxc3xa9rieure de physique et chimie industrielles (PSL University) and CNRS, 75005, Paris, France.|Protein Physiology Lab, Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Quxc3xadmica Biolxc3xb3gica, Buenos Aires, Argentina.|Laboratoire de physique de l\\xc3x89cole normale supxc3xa9rieure (PSL University), CNRS, Sorbonne Universitxc3xa9, and Universitxc3xa9 de Paris, 75005 Paris, France.|Laboratoire de physique de l\\xc3x89cole normale supxc3xa9rieure (PSL University), CNRS, Sorbonne Universitxc3xa9, and Universitxc3xa9 de Paris, 75005 Paris, France.', 'France|Argentina|France|Argentina|France|France', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007282', '31415557', 'The coding space of protein sequences is shaped by evolutionary constraints set by requirements of function and stability. We show that the coding space of a given protein family-the total number of sequences in that family-can be estimated using models of maximum entropy trained on multiple sequence alignments of naturally occuring amino acid sequences. We analyzed and calculated the size of three abundant repeat proteins families, whose members are large proteins made of many repetitions of conserved portions of xe2x88xbc30 amino acids. While amino acid conservation at each position of the alignment explains most of the reduction of diversity relative to completely random sequences, we found that correlations between amino acid usage at different positions significantly impact that diversity. We quantified the impact of different types of correlations, functional and evolutionary, on sequence diversity. Analysis of the detailed structure of the coding space of the families revealed a rugged landscape, with many local energy minima of varying sizes with a hierarchical structure, reminiscent of fustrated energy landscapes of spin glass in physics. This clustered structure indicates a multiplicity of subtypes within each family, and suggests new strategies for protein design.'),
(89871, 2019, 'plos', 'FAMoS: A Flexible and dynamic Algorithm for Model Selection to analyse complex systems dynamics', 'Gabel, Michael|Hohl, Tobias|Imle, Andrea|Fackler, Oliver T|Graw, Frederik', 'Center for Modelling and Simulation in the Biosciences, BioQuant-Center, Heidelberg University, Heidelberg, Germany.|Center for Modelling and Simulation in the Biosciences, BioQuant-Center, Heidelberg University, Heidelberg, Germany.|Department of Infectious Diseases, Centre for Integrative Infectious Disease Research (CIID), Integrative Virology, University Hospital Heidelberg, Heidelberg, Germany.|Department of Infectious Diseases, Centre for Integrative Infectious Disease Research (CIID), Integrative Virology, University Hospital Heidelberg, Heidelberg, Germany.|Center for Modelling and Simulation in the Biosciences, BioQuant-Center, Heidelberg University, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007230', '31419221', 'Most biological systems are difficult to analyse due to a multitude of interacting components and the concomitant lack of information about the essential dynamics. Finding appropriate models that provide a systematic description of such biological systems and that help to identify their relevant factors and processes can be challenging given the sheer number of possibilities. Model selection algorithms that evaluate the performance of a multitude of different models against experimental data provide a useful tool to identify appropriate model structures. However, many algorithms addressing the analysis of complex dynamical systems, as they are often used in biology, compare a preselected number of models or rely on exhaustive searches of the total model space which might be unfeasible dependent on the number of possibilities. Therefore, we developed an algorithm that is able to perform model selection on complex systems and searches large model spaces in a dynamical way. Our algorithm includes local and newly developed non-local search methods that can prevent the algorithm from ending up in local minima of the model space by accounting for structurally similar processes. We tested and validated the algorithm based on simulated data and showed its flexibility for handling different model structures. We also used the algorithm to analyse experimental data on the cell proliferation dynamics of CD4+ and CD8+ T cells that were cultured under different conditions. Our analyses indicated dynamical changes within the proliferation potential of cells that was reduced within tissue-like 3D ex vivo cultures compared to suspension. Due to the flexibility in handling various model structures, the algorithm is applicable to a large variety of different biological problems and represents a useful tool for the data-oriented evaluation of complex model spaces.'),
(89872, 2019, 'plos', 'Characterising antibody kinetics from multiple influenza infection and vaccination events in ferrets', 'Hay, James A|Laurie, Karen|White, Michael|Riley, Steven', 'MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.|WHO Collaborating Centre for Reference and Research on Influenza, Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.|Malaria: Parasites and Hosts, Department of Parasites and Insect Vectors, Institut Pasteur, Paris, France.|MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.', 'United Kingdom|Australia|France|United Kingdom', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007294', '31425503', 'The strength and breadth of an individuals antibody repertoire is an important predictor of their response to influenza infection or vaccination. Although progress has been made in understanding qualitatively how repeated exposures shape the antibody mediated immune response, quantitative understanding remains limited. We developed a set of mathematical models describing short-term antibody kinetics following influenza infection or vaccination and fit them to haemagglutination inhibition (HI) titres from 5 groups of ferrets which were exposed to different combinations of trivalent inactivated influenza vaccine (TIV with or without adjuvant), A/H3N2 priming inoculation and post-vaccination A/H1N1 inoculation. We fit models with various immunological mechanisms that have been empirically observed but have not previously been included in mathematical models of antibody landscapes, including: titre ceiling effects, antigenic seniority and exposure-type specific cross reactivity. Based on the parameter estimates of the best supported models, we describe a number of key immunological features. We found quantifiable differences in the degree of homologous and cross-reactive antibody boosting elicited by different exposure types. Infection and adjuvanted vaccination generally resulted in strong, broadly reactive responses whereas unadjuvanted vaccination resulted in a weak, narrow response. We found that the order of exposure mattered: priming with A/H3N2 improved subsequent vaccine response, and the second dose of adjuvanted vaccination resulted in substantially greater antibody boosting than the first. Either antigenic seniority or a titre ceiling effect were included in the two best fitting models, suggesting a role for a mechanism describing diminishing antibody boosting with repeated exposures. Although there was considerable uncertainty in our estimates of antibody waning parameters, our results suggest that both short and long term waning were present and would be identifiable with a larger set of experiments. These results highlight the potential use of repeat exposure animal models in revealing short-term, strain-specific immune dynamics of influenza.'),
(89873, 2019, 'plos', 'PRAS: Predicting functional targets of RNA binding proteins based on CLIP-seq peaks', 'Lin, Jianan|Zhang, Yuping|Frankel, Wayne N|Ouyang, Zhengqing', 'The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America.|Department of Statistics, University of Connecticut, Storrs, Connecticut, United States of America.|Department of Genetics and Development and Institute for Genomic Medicine, Columbia University Medical Center, New York City, New York, United States of America.|The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America.', 'United States|United States|United States|United States', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007227', '31425505', 'RNA-protein interaction plays important roles in post-transcriptional regulation. Recent advancements in cross-linking and immunoprecipitation followed by sequencing (CLIP-seq) technologies make it possible to detect the binding peaks of a given RNA binding protein (RBP) at transcriptome scale. However, it is still challenging to predict the functional consequences of RBP binding peaks. In this study, we propose the Protein-RNA Association Strength (PRAS), which integrates the intensities and positions of the binding peaks of RBPs for functional mRNA targets prediction. We illustrate the superiority of PRAS over existing approaches on predicting the functional targets of two related but divergent CELF (CUGBP, ELAV-like factor) RBPs in mouse brain and muscle. We also demonstrate the potential of PRAS for wide adoption by applying it to the enhanced CLIP-seq (eCLIP) datasets of 37 RNA decay related RBPs in two human cell lines. PRAS can be utilized to investigate any RBPs with available CLIP-seq peaks. PRAS is freely available at http://ouyanglab.jax.org/pras/.'),
(89874, 2019, 'plos', 'Simulation of calcium signaling in fine astrocytic processes: Effect of spatial properties on spontaneous activity', 'Denizot, Audrey|Arizono, Misa|Nägerl, U Valentin|Soula, Hédi|Berry, Hugues', 'INRIA, F-69603, Villeurbanne, France.|Interdisciplinary Institute for Neuroscience, Université de Bordeaux, Bordeaux, France.|Interdisciplinary Institute for Neuroscience, Université de Bordeaux, Bordeaux, France.|INRIA, F-69603, Villeurbanne, France.|INRIA, F-69603, Villeurbanne, France.', 'France|France|France|France|France', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1006795', '31425510', 'Astrocytes, a glial cell type of the central nervous system, have emerged as detectors and regulators of neuronal information processing. Astrocyte excitability resides in transient variations of free cytosolic calcium concentration over a range of temporal and spatial scales, from sub-microdomains to waves propagating throughout the cell. Despite extensive experimental approaches, it is not clear how these signals are transmitted to and integrated within an astrocyte. The localization of the main molecular actors and the geometry of the system, including the spatial organization of calcium channels IP3R, are deemed essential. However, as most calcium signals occur in astrocytic ramifications that are too fine to be resolved by conventional light microscopy, most of those spatial data are unknown and computational modeling remains the only methodology to study this issue. Here, we propose an IP3R-mediated calcium signaling model for dynamics in such small sub-cellular volumes. To account for the expected stochasticity and low copy numbers, our model is both spatially explicit and particle-based. Extensive simulations show that spontaneous calcium signals arise in the model via the interplay between excitability and stochasticity. The model reproduces the main forms of calcium signals and indicates that their frequency crucially depends on the spatial organization of the IP3R channels. Importantly, we show that two processes expressing exactly the same calcium channels can display different types of calcium signals depending on the spatial organization of the channels. Our model with realistic process volume and calcium concentrations successfully reproduces spontaneous calcium signals that we measured in calcium micro-domains with confocal microscopy and predicts that local variations of calcium indicators might contribute to the diversity of calcium signals observed in astrocytes. To our knowledge, this model is the first model suited to investigate calcium dynamics in fine astrocytic processes and to propose plausible mechanisms responsible for their variability.'),
(89875, 2019, 'plos', 'TeXP: Deconvolving the effects of pervasive and autonomous transcription of transposable elements', 'Navarro, Fabio Cp|Hoops, Jacob|Bellfy, Lauren|Cerveira, Eliza|Zhu, Qihui|Zhang, Chengsheng|Lee, Charles|Gerstein, Mark B', 'Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America.|Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America.|The Jackson Laboratory for Genomic Medicine, Farmington, Michigan, United States of America.|The Jackson Laboratory for Genomic Medicine, Farmington, Michigan, United States of America.|The Jackson Laboratory for Genomic Medicine, Farmington, Michigan, United States of America.|The Jackson Laboratory for Genomic Medicine, Farmington, Michigan, United States of America.|The Jackson Laboratory for Genomic Medicine, Farmington, Michigan, United States of America.|Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 4, '-', 'Journal Article', '10.1371/journal.pcbi.1007293', '31425522', 'The Long interspersed nuclear element 1 (LINE-1) is a primary source of genetic variation in humans and other mammals. Despite its importance, LINE-1 activity remains difficult to study because of its highly repetitive nature. Here, we developed and validated a method called TeXP to gauge LINE-1 activity accurately. TeXP builds mappability signatures from LINE-1 subfamilies to deconvolve the effect of pervasive transcription from autonomous LINE-1 activity. In particular, it apportions the multiple reads aligned to the many LINE-1 instances in the genome into these two categories. Using our method, we evaluated well-established cell lines, cell-line compartments and healthy tissues and found that the vast majority (91.7%) of transcriptome reads overlapping LINE-1 derive from pervasive transcription. We validated TeXP by independently estimating the levels of LINE-1 autonomous transcription using ddPCR, finding high concordance. Next, we applied our method to comprehensively measure LINE-1 activity across healthy somatic cells, while backing out the effect of pervasive transcription. Unexpectedly, we found that LINE-1 activity is present in many normal somatic cells. This finding contrasts with earlier studies showing that LINE-1 has limited activity in healthy somatic tissues, except for neuroprogenitor cells. Interestingly, we found that the amount of LINE-1 activity was associated with the with the amount of cell turnover, with tissues with low cell turnover rates (e.g. the adult central nervous system) showing lower LINE-1 activity. Altogether, our results show how accounting for pervasive transcription is critical to accurately quantify the activity of highly repetitive regions of the human genome.'),
(89876, 2019, 'plos', 'Uncertainty reduction in biochemical kinetic models: Enforcing desired model properties', 'Miskovic, Ljubisa|Béal, Jonas|Moret, Michael|Hatzimanikatis, Vassily', 'Laboratory of Computational Systems Biology (LCSB), EPFL, CH, Lausanne, Switzerland.|Masters Program in Life Sciences and Technology, EPFL, CH, Lausanne, Switzerland.|Masters Program in Life Sciences and Technology, EPFL, CH, Lausanne, Switzerland.|Laboratory of Computational Systems Biology (LCSB), EPFL, CH, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007242', '31430276', 'A persistent obstacle for constructing kinetic models of metabolism is uncertainty in the kinetic properties of enzymes. Currently, available methods for building kinetic models can cope indirectly with uncertainties by integrating data from different biological levels and origins into models. In this study, we use the recently proposed computational approach iSCHRUNK (in Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models), which combines Monte Carlo parameter sampling methods and machine learning techniques, in the context of Bayesian inference. Monte Carlo parameter sampling methods allow us to exploit synergies between different data sources and generate a population of kinetic models that are consistent with the available data and physicochemical laws. The machine learning allows us to data-mine the a priori generated kinetic parameters together with the integrated datasets and derive posterior distributions of kinetic parameters consistent with the observed physiology. In this work, we used iSCHRUNK to address a design question: can we identify which are the kinetic parameters and what are their values that give rise to a desired metabolic behavior? Such information is important for a wide variety of studies ranging from biotechnology to medicine. To illustrate the proposed methodology, we performed Metabolic Control Analysis, computed the flux control coefficients of the xylose uptake (XTR), and identified parameters that ensure a rate improvement of XTR in a glucose-xylose co-utilizing S. cerevisiae strain. Our results indicate that only three kinetic parameters need to be accurately characterized to describe the studied physiology, and ultimately to design and control the desired responses of the metabolism. This framework paves the way for a new generation of methods that will systematically integrate the wealth of available omics data and efficiently extract the information necessary for metabolic engineering and synthetic biology decisions.'),
(89877, 2019, 'plos', 'Learning to synchronize: How biological agents can couple neural task modules for dealing with the stability-plasticity dilemma', 'Verbeke, Pieter|Verguts, Tom', 'Department of Experimental Psychology, Ghent University, Ghent, Belgium.|Department of Experimental Psychology, Ghent University, Ghent, Belgium.', 'Belgium|Belgium', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1006604', '31430280', 'We provide a novel computational framework on how biological and artificial agents can learn to flexibly couple and decouple neural task modules for cognitive processing. In this way, they can address the stability-plasticity dilemma. For this purpose, we combine two prominent computational neuroscience principles, namely Binding by Synchrony and Reinforcement Learning. The model learns to synchronize task-relevant modules, while also learning to desynchronize currently task-irrelevant modules. As a result, old (but currently task-irrelevant) information is protected from overwriting (stability) while new information can be learned quickly in currently task-relevant modules (plasticity). We combine learning to synchronize with task modules that learn via one of several classical learning algorithms (Rescorla-Wagner, backpropagation, Boltzmann machines). The resulting combined model is tested on a reversal learning paradigm where it must learn to switch between three different task rules. We demonstrate that our combined model has significant computational advantages over the original network without synchrony, in terms of both stability and plasticity. Importantly, the resulting models processing dynamics are also consistent with empirical data and provide empirically testable hypotheses for future MEG/EEG studies.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89878, 2019, 'plos', 'Transient crosslinking kinetics optimize gene cluster interactions', 'Walker, Benjamin|Taylor, Dane|Lawrimore, Josh|Hult, Caitlin|Adalsteinsson, David|Bloom, Kerry|Forest, M Gregory', 'Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Mathematics, University at Buffalo, State University of New York, Buffalo, New York, United States of America.|Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.|Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007124', '31433796', 'Our understanding of how chromosomes structurally organize and dynamically interact has been revolutionized through the lens of long-chain polymer physics. Major protein contributors to chromosome structure and dynamics are condensin and cohesin that stochastically generate loops within and between chains, and entrap proximal strands of sister chromatids. In this paper, we explore the ability of transient, protein-mediated, gene-gene crosslinks to induce clusters of genes, thereby dynamic architecture, within the highly repeated ribosomal DNA that comprises the nucleolus of budding yeast. We implement three approaches: live cell microscopy, computational modeling of the full genome during G1 in budding yeast, exploring four decades of timescales for transient crosslinks between 5kbp domains (genes) in the nucleolus on Chromosome XII, and, temporal network models with automated community (cluster) detection algorithms applied to the full range of 4D modeling datasets. The data analysis tools detect and track gene clusters, their size, number, persistence time, and their plasticity (deformation). Of biological significance, our analysis reveals an optimal mean crosslink lifetime that promotes pairwise and cluster gene interactions through flexible clustering. In this state, large gene clusters self-assemble yet frequently interact (merge and separate), marked by gene exchanges between clusters, which in turn maximizes global gene interactions in the nucleolus. This regime stands between two limiting cases each with far less global gene interactions: with shorter crosslink lifetimes, rigid clustering emerges with clusters that interact infrequently, with longer crosslink lifetimes, there is a dissolution of clusters. These observations are compared with imaging experiments on a normal yeast strain and two condensin-modified mutant cell strains. We apply the same image analysis pipeline to the experimental and simulated datasets, providing support for the modeling predictions.'),
(89879, 2019, 'plos', 'Integrating Hi-C links with assembly graphs for chromosome-scale assembly', 'Ghurye, Jay|Rhie, Arang|Walenz, Brian P|Schmitt, Anthony|Selvaraj, Siddarth|Pop, Mihai|Phillippy, Adam M|Koren, Sergey', 'Department of Computer Science, University of Maryland, College Park, Maryland, United States of America.|Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institute of Health, Bethesda, Maryland, United States of America.|Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institute of Health, Bethesda, Maryland, United States of America.|Arima Genomics, San Diego, California, United States of America.|Arima Genomics, San Diego, California, United States of America.|Department of Computer Science, University of Maryland, College Park, Maryland, United States of America.|Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institute of Health, Bethesda, Maryland, United States of America.|Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institute of Health, Bethesda, Maryland, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 14, '-', 'Journal Article', '10.1371/journal.pcbi.1007273', '31433799', 'Long-read sequencing and novel long-range assays have revolutionized de novo genome assembly by automating the reconstruction of reference-quality genomes. In particular, Hi-C sequencing is becoming an economical method for generating chromosome-scale scaffolds. Despite its increasing popularity, there are limited open-source tools available. Errors, particularly inversions and fusions across chromosomes, remain higher than alternate scaffolding technologies. We present a novel open-source Hi-C scaffolder that does not require an a priori estimate of chromosome number and minimizes errors by scaffolding with the assistance of an assembly graph. We demonstrate higher accuracy than the state-of-the-art methods across a variety of Hi-C library preparations and input assembly sizes. The Python and C++ code for our method is openly available at https://github.com/machinegun/SALSA.'),
(89880, 2019, 'plos', 'Gaussian curvature and the budding kinetics of enveloped viruses', 'Dharmavaram, Sanjay|She, Selene Baochen|Lázaro, Guillermo|Hagan, Michael Francis|Bruinsma, Robijn', 'Department of Mathematics, Bucknell University, Lewisburg, Pennsylvania, United States of America.|Department of Physics and Astronomy, University of California, Los Angeles, Los Angeles, California, United States of America.|Martin A. Fisher School of Physics, Brandeis University, Waltham, Massachusetts, United States of America.|Martin A. Fisher School of Physics, Brandeis University, Waltham, Massachusetts, United States of America.|Department of Physics and Astronomy, University of California, Los Angeles, Los Angeles, California, United States of America.', 'United States|United States|United States|United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006602', '31433804', 'The formation of a membrane-enveloped virus starts with the assembly of a curved layer of capsid proteins lining the interior of the plasma membrane (PM) of the host cell. This layer develops into a spherical shell (capsid) enveloped by a lipid-rich membrane. In many cases, the budding process stalls prior to the release of the virus. Recently, Brownian dynamics simulations of a coarse-grained model system reproduced protracted pausing and stalling, which suggests that the origin of pausing/stalling is to be found in the physics of the budding process. Here, we propose that the pausing/stalling observed in the simulations can be understood as a purely kinetic phenomenon associated with the neck geometry. A geometrical potential energy barrier develops during the budding that must be overcome by capsid proteins diffusing along the membrane prior to incorporation into the capsid. The barrier is generated by a conflict between the positive Gauss curvature of the assembling capsid and the negative Gauss curvature of the neck region. A continuum theory description is proposed and is compared with the Brownian simulations of the budding of enveloped viruses.'),
(89881, 2019, 'plos', 'Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI', 'Koppe, Georgia|Toutounji, Hazem|Kirsch, Peter|Lis, Stefanie|Durstewitz, Daniel', 'Department of Theoretical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.|Department of Theoretical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.|Department of Clinical Psychology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.|Institute for Psychiatric and Psychosomatic Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.|Department of Theoretical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007263', '31433810', 'A major tenet in theoretical neuroscience is that cognitive and behavioral processes are ultimately implemented in terms of the neural system dynamics. Accordingly, a major aim for the analysis of neurophysiological measurements should lie in the identification of the computational dynamics underlying task processing. Here we advance a state space model (SSM) based on generative piecewise-linear recurrent neural networks (PLRNN) to assess dynamics from neuroimaging data. In contrast to many other nonlinear time series models which have been proposed for reconstructing latent dynamics, our model is easily interpretable in neural terms, amenable to systematic dynamical systems analysis of the resulting set of equations, and can straightforwardly be transformed into an equivalent continuous-time dynamical system. The major contributions of this paper are the introduction of a new observation model suitable for functional magnetic resonance imaging (fMRI) coupled to the latent PLRNN, an efficient stepwise training procedure that forces the latent model to capture the true underlying dynamics rather than just fitting (or predicting) the observations, and of an empirical measure based on the Kullback-Leibler divergence to evaluate from empirical time series how well this goal of approximating the underlying dynamics has been achieved. We validate and illustrate the power of our approach on simulated ground-truth dynamical systems as well as on experimental fMRI time series, and demonstrate that the learnt dynamics harbors task-related nonlinear structure that a linear dynamical model fails to capture. Given that fMRI is one of the most common techniques for measuring brain activity non-invasively in human subjects, this approach may provide a novel step toward analyzing aberrant (nonlinear) dynamics for clinical assessment or neuroscientific research.'),
(89882, 2019, 'plos', 'Variation in plastic responses to light results from selection in different competitive environments-A game theoretical approach using virtual plants', 'Bongers, Franca J|Douma, Jacob C|Iwasa, Yoh|Pierik, Ronald|Evers, Jochem B|Anten, Niels P R', 'Centre for Crop Systems Analysis, Wageningen University, Wageningen, The Netherlands.|Centre for Crop Systems Analysis, Wageningen University, Wageningen, The Netherlands.|Theoretical Biology, Kyushu University, Fukuoka, Japan.|Plant Ecophysiology, Utrecht University, Utrecht, the Netherlands.|Centre for Crop Systems Analysis, Wageningen University, Wageningen, The Netherlands.|Centre for Crop Systems Analysis, Wageningen University, Wageningen, The Netherlands.', 'Netherlands|Netherlands|Japan|Netherlands|Netherlands|Netherlands', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007253', '31433817', 'Phenotypic plasticity is a vital strategy for plants to deal with changing conditions by inducing phenotypes favourable in different environments. Understanding how natural selection acts on variation in phenotypic plasticity in plants is therefore a central question in ecology, but is often ignored in modelling studies. Here we present a new modelling approach that allows for the analysis of selection for variation in phenotypic plasticity as a response strategy. We assess selection for shade avoidance strategies of Arabidopsis thaliana in response to future neighbour shading signalled through a decrease in red:far-red (R:FR) ratio. For this, we used a spatially explicit 3D virtual plant model that simulates individual Arabidopsis plants competing for light in different planting densities. Plant structure and growth were determined by the organ-specific interactions with the light environment created by the vegetation structure itself. Shade avoidance plastic responses were defined by a plastic response curve relating petiole elongation and lamina growth to R:FR perceived locally. Different plasticity strategies were represented by different shapes of the response curve that expressed different levels of R:FR sensitivity. Our analyses show that the shape of the selected shade avoidance strategy varies with planting density. At higher planting densities, more sensitive response curves are selected for than at lower densities. In addition, the balance between lamina and petiole responses influences the sensitivity of the response curves selected for. Combining computational virtual plant modelling with a game theoretical analysis represents a new step towards analysing how natural selection could have acted upon variation in shade avoidance as a response strategy, which can be linked to genetic variation and underlying physiological processes.'),
(89883, 2019, 'plos', 'ProtFus: A Comprehensive Method Characterizing Protein-Protein Interactions of Fusion Proteins', 'Tagore, Somnath|Gorohovski, Alessandro|Jensen, Lars Juhl|Frenkel-Morgenstern, Milana', 'The Cancer Genomics and BioComputing of Complex Diseases lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel.|The Cancer Genomics and BioComputing of Complex Diseases lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel.|Cellular Network Biology Group, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.|The Cancer Genomics and BioComputing of Complex Diseases lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel.', 'Israel|Israel|Denmark|Israel', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007239', '31437145', 'Tailored therapy aims to cure cancer patients effectively and safely, based on the complex interactions between patients genomic features, disease pathology and drug metabolism. Thus, the continual increase in scientific literature drives the need for efficient methods of data mining to improve the extraction of useful information from texts based on patients genomic features. An important application of text mining to tailored therapy in cancer encompasses the use of mutations and cancer fusion genes as moieties that change patients cellular networks to develop cancer, and also affect drug metabolism. Fusion proteins, which are derived from the slippage of two parental genes, are produced in cancer by chromosomal aberrations and trans-splicing. Given that the two parental proteins for predicted fusion proteins are known, we used our previously developed method for identifying chimeric protein-protein interactions (ChiPPIs) associated with the fusion proteins. Here, we present a validation approach that receives fusion proteins of interest, predicts their cellular network alterations by ChiPPI and validates them by our new method, ProtFus, using an online literature search. This process resulted in a set of 358 fusion proteins and their corresponding protein interactions, as a training set for a Naïve Bayes classifier, to identify predicted fusion proteins that have reliable evidence in the literature and that were confirmed experimentally. Next, for a test group of 1817 fusion proteins, we were able to identify from the literature 2908 PPIs in total, across 18 cancer types. The described method, ProtFus, can be used for screening the literature to identify unique cases of fusion proteins and their PPIs, as means of studying alterations of protein networks in cancers. Availability: http://protfus.md.biu.ac.il/.'),
(89884, 2019, 'plos', 'Twelve quick tips for designing sound dynamical models for bioprocesses', 'Mairet, Francis|Bernard, Olivier', 'Ifremer, Physiology and Biotechnology of Algae laboratory, Nantes, France.|Côte dAzur University, INRIA, BIOCORE, Sophia-Antipolis Cedex, France.', 'France|France', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007222', '31437146', 'Because of the inherent complexity of bioprocesses, mathematical models are more and more used for process design, control, optimization, etc. These models are generally based on a set of biochemical reactions. Model equations are then derived from mass balance, coupled with empirical kinetics. Biological models are nonlinear and represent processes, which by essence are dynamic and adaptive. The temptation to embed most of the biology is high, with the risk that calibration would not be significant anymore. The most important task for a modeler is thus to ensure a balance between model complexity and ease of use. Since a model should be tailored to the objectives, which will depend on applications and environment, a universal model representing any possible situation is probably not the best option.'),
(89885, 2019, 'plos', 'A mathematical model of calcium dynamics: Obesity and mitochondria-associated ER membranes', 'Han, Jung Min|Periwal, Vipul', 'Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006661', '31437152', 'Multiple cellular organelles tightly orchestrate intracellular calcium (Ca2+) dynamics to regulate cellular activities and maintain homeostasis. The interplay between the endoplasmic reticulum (ER), a major store of intracellular Ca2+, and mitochondria, an important source of adenosine triphosphate (ATP), has been the subject of much research, as their dysfunction has been linked with metabolic diseases. Interestingly, throughout the cells cytosolic domain, these two organelles share common microdomains called mitochondria-associated ER membranes (MAMs), where their membranes are in close apposition. The role of MAMs is critical for intracellular Ca2+ dynamics as they provide hubs for direct Ca2+ exchange between the organelles. A recent experimental study reported correlation between obesity and MAM formation in mouse liver cells, and obesity-related cellular changes that are closely associated with the regulation of Ca2+ dynamics. We constructed a mathematical model to study the effects of MAM Ca2+ dynamics on global Ca2+ activities. Through a series of model simulations, we investigated cellular mechanisms underlying the altered Ca2+ dynamics in the cells under obesity. We predict that, as the dosage of stimulus gradually increases, liver cells from obese mice will reach the state of saturated cytosolic Ca2+ concentration at a lower stimulus concentration, compared to cells from healthy mice.'),
(89886, 2019, 'plos', 'A computational model for gonadotropin releasing cells in the teleost fish medaka', 'Halnes, Geir|Tennøe, Simen|Haug, Trude M|Einevoll, Gaute T|Weltzien, Finn-Arne|Hodne, Kjetil', 'Faculty for Science and Technology, Norwegian University of Life Sciences, Ås, Norway.|Centre for Integrative Neuroplasticity, University of Oslo, Oslo, Norway.|Institute of Oral Biology, University of Oslo, Oslo, Norway.|Faculty for Science and Technology, Norwegian University of Life Sciences, Ås, Norway.|Department of Basic Sciences and Aquatic Medicine, Norwegian University of Life Sciences, Campus Adamstuen, Oslo, Norway.|Department of Basic Sciences and Aquatic Medicine, Norwegian University of Life Sciences, Campus Adamstuen, Oslo, Norway.', 'Norway|Norway|Norway|Norway|Norway|Norway', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006662', '31437161', 'Pituitary endocrine cells fire action potentials (APs) to regulate their cytosolic Ca2+ concentration and hormone secretion rate. Depending on animal species, cell type, and biological conditions, pituitary APs are generated either by TTX-sensitive Na+ currents (INa), high-voltage activated Ca2+ currents (ICa), or by a combination of the two. Previous computational models of pituitary cells have mainly been based on data from rats, where INa is largely inactivated at the resting potential, and spontaneous APs are predominantly mediated by ICa. Unlike in rats, spontaneous INa-mediated APs are consistently seen in pituitary cells of several other animal species, including several species of fish. In the current work we develop a computational model of gonadotropin releasing cells in the teleost fish medaka (Oryzias latipes). The model stands out from previous modeling efforts by being (1) the first model of a pituitary cell in teleosts, (2) the first pituitary cell model that fires sponateous APs that are predominantly mediated by INa, and (3) the first pituitary cell model where the kinetics of the depolarizing currents, INa and ICa, are directly fitted to voltage-clamp data. We explore the firing properties of the model, and compare it to the properties of previous models that fire ICa-based APs. We put a particular focus on how the big conductance K+ current (IBK) modulates the AP shape. Interestingly, we find that IBK can prolong AP duration in models that fire ICa-based APs, while it consistently shortens the duration of the predominantly INa-mediated APs in the medaka gonadotroph model. Although the model is constrained to experimental data from gonadotroph cells in medaka, it may likely provide insights also into other pituitary cell types that fire INa-mediated APs.'),
(89887, 2019, 'plos', 'Optimizing antibody affinity and stability by the automated design of the variable light-heavy chain interfaces', 'Warszawski, Shira|Borenstein Katz, Aliza|Lipsh, Rosalie|Khmelnitsky, Lev|Ben Nissan, Gili|Javitt, Gabriel|Dym, Orly|Unger, Tamar|Knop, Orli|Albeck, Shira|Diskin, Ron|Fass, Deborah|Sharon, Michal|Fleishman, Sarel J', 'Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.|Department of Structural Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.|Department of Structural Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.|Department of Structural Biology, Weizmann Institute of Science, Rehovot, Israel.|Israel Structural Proteomics Center, Weizmann Institute of Science, Rehovot, Israel.|Israel Structural Proteomics Center, Weizmann Institute of Science, Rehovot, Israel.|Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.|Israel Structural Proteomics Center, Weizmann Institute of Science, Rehovot, Israel.|Department of Structural Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Structural Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.|Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1007207', '31442220', 'Antibodies developed for research and clinical applications may exhibit suboptimal stability, expressibility, or affinity. Existing optimization strategies focus on surface mutations, whereas natural affinity maturation also introduces mutations in the antibody core, simultaneously improving stability and affinity. To systematically map the mutational tolerance of an antibody variable fragment (Fv), we performed yeast display and applied deep mutational scanning to an anti-lysozyme antibody and found that many of the affinity-enhancing mutations clustered at the variable light-heavy chain interface, within the antibody core. Rosetta design combined enhancing mutations, yielding a variant with tenfold higher affinity and substantially improved stability. To make this approach broadly accessible, we developed AbLIFT, an automated web server that designs multipoint core mutations to improve contacts between specific Fv light and heavy chains (http://AbLIFT.weizmann.ac.il). We applied AbLIFT to two unrelated antibodies targeting the human antigens VEGF and QSOX1. Strikingly, the designs improved stability, affinity, and expression yields. The results provide proof-of-principle for bypassing laborious cycles of antibody engineering through automated computational affinity and stability design.'),
(89888, 2019, 'plos', 'Cooperative adaptation to therapy (CAT) confers resistance in heterogeneous non-small cell lung cancer', 'Craig, Morgan|Kaveh, Kamran|Woosley, Alec|Brown, Andrew S|Goldman, David|Eton, Elliot|Mehta, Ravindra M|Dhawan, Andrew|Arai, Kazuya|Rahman, M Mamunur|Chen, Sidi|Nowak, Martin A|Goldman, Aaron', 'Département de mathématiques et de statistique, Université de Montréal, Montréal, Canada.|Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts, United States of America.|Computational Genomics Division, Arrayo, Boston, Massachusetts, United States of America.|Computational Genomics Division, Arrayo, Boston, Massachusetts, United States of America.|7730E BlackCrest Pl., Tucson, Arizona, United States of America.|Division of Engineering in Medicine, Brigham and Womens Hospital, Boston, Massachusetts, United States of America.|Interventional Pulmonology and Critical Care Medicine, Apollo Speciality Hospitals, Bengaluru, India.|Neurological Institute, Cleveland Clinic, Cleveland, Ohio, United States of America.|JSR Life Sciences Corporation, Tsukuba, Japan.|MBL International, Woburn, Massachusetts, United States of America.|Department of Genetics and Systems Biology Institute, Yale University, New Haven, Connecticut, United States of America.|Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts, United States of America.|Division of Engineering in Medicine, Brigham and Womens Hospital, Boston, Massachusetts, United States of America.', 'Canada|United States|United States|United States|United States|United States|India|United States|Jap', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007278', '31449515', 'Understanding intrinsic and acquired resistance is crucial to overcoming cancer chemotherapy failure. While it is well-established that intratumor, subclonal genetic and phenotypic heterogeneity significantly contribute to resistance, it is not fully understood how tumor sub-clones interact with each other to withstand therapy pressure. Here, we report a previously unrecognized behavior in heterogeneous tumors: cooperative adaptation to therapy (CAT), in which cancer cells induce co-resistant phenotypes in neighboring cancer cells when exposed to cancer therapy. Using a CRISPR/Cas9 toolkit we engineered phenotypically diverse non-small cell lung cancer (NSCLC) cells by conferring mutations in Dicer1, a type III cytoplasmic endoribonuclease involved in small non-coding RNA genesis. We monitored three-dimensional growth dynamics of fluorescently-labeled mutant and/or wild-type cells individually or in co-culture using a substrate-free NanoCulture system under unstimulated or drug pressure conditions. By integrating mathematical modeling with flow cytometry, we characterized the growth patterns of mono- and co-cultures using a mathematical model of intra- and interspecies competition. Leveraging the flow cytometry data, we estimated the models parameters to reveal that the combination of WT and mutants in co-cultures allowed for beneficial growth in previously drug sensitive cells despite drug pressure via induction of cell state transitions described by a cooperative game theoretic change in the fitness values. Finally, we used an ex vivo human tumor model that predicts clinical response through drug sensitivity analyses and determined that cellular and morphologic heterogeneity correlates to prognostic failure of multiple clinically-approved and off-label drugs in individual NSCLC patient samples. Together, these findings present a new paradox in drug resistance implicating non-genetic cooperation among tumor cells to thwart drug pressure, suggesting that profiling for druggable targets (i.e. mutations) alone may be insufficient to assign effective therapy.'),
(89889, 2019, 'plos', 'CNEr: A toolkit for exploring extreme noncoding conservation', 'Tan, Ge|Polychronopoulos, Dimitris|Lenhard, Boris', 'Computational Regulatory Genomics Group, MRC London Institute of Medical Sciences, United Kingdom.|Computational Regulatory Genomics Group, MRC London Institute of Medical Sciences, United Kingdom.|Computational Regulatory Genomics Group, MRC London Institute of Medical Sciences, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1006940', '31449516', 'Conserved Noncoding Elements (CNEs) are elements exhibiting extreme noncoding conservation in Metazoan genomes. They cluster around developmental genes and act as long-range enhancers, yet nothing that we know about their function explains the observed conservation levels. Clusters of CNEs coincide with topologically associating domains (TADs), indicating ancient origins and stability of TAD locations. This has suggested further hypotheses about the still elusive origin of CNEs, and has provided a comparative genomics-based method of estimating the position of TADs around developmentally regulated genes in genomes where chromatin conformation capture data is missing. To enable researchers in gene regulation and chromatin biology to start deciphering this phenomenon, we developed CNEr, a R/Bioconductor toolkit for large-scale identification of CNEs and for studying their genomic properties. We apply CNEr to two novel genome comparisons-fruit fly vs tsetse fly, and two sea urchin genomes-and report novel insights gained from their analysis. We also show how to reveal interesting characteristics of CNEs by coupling CNEr with existing Bioconductor packages. CNEr is available at Bioconductor (https://bioconductor.org/packages/CNEr/) and maintained at github (https://github.com/ge11232002/CNEr).'),
(89890, 2019, 'plos', 'Selective recruitment of cortical neurons by electrical stimulation', 'Komarov, Maxim|Malerba, Paola|Golden, Ryan|Nunez, Paul|Halgren, Eric|Bazhenov, Maxim', 'Department of Medicine, University of California, San Diego, La Jolla, California, United States of America.|Department of Medicine, University of California, San Diego, La Jolla, California, United States of America.|Department of Medicine, University of California, San Diego, La Jolla, California, United States of America.|Department of Biomedical Engineering, Tulane University, New Orleans, Louisiana, United States of America.|Department of Neurosciences, University of California, San Diego, La Jolla, California, United States of America.|Department of Medicine, University of California, San Diego, La Jolla, California, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007277', '31449517', 'Despite its critical importance in experimental and clinical neuroscience, at present there is no systematic method to predict which neural elements will be activated by a given stimulation regime. Here we develop a novel approach to model the effect of cortical stimulation on spiking probability of neurons in a volume of tissue, by applying an analytical estimate of stimulation-induced activation of different cell types across cortical layers. We utilize the morphology and properties of axonal arborization profiles obtained from publicly available anatomical reconstructions of the twelve main categories of neocortical neurons to derive the dependence of activation probability on cell type, layer and distance from the source. We then propagate this activity through the local network incorporating connectivity, synaptic and cellular properties. Our work predicts that (a) intracranial cortical stimulation induces selective activation across cell types and layers, (b) superficial anodal stimulation is more effective than cathodal at cell activation, (c) cortical surface stimulation focally activates layer I axons, and (d) there is an optimal stimulation intensity capable of eliciting cell activation lasting beyond the end of stimulation. We conclude that selective effects of cortical electrical stimulation across cell types and cortical layers are largely driven by their different axonal arborization and myelination profiles.'),
(89891, 2019, 'plos', 'A lipophilicity-based energy function for membrane-protein modelling and design', 'Weinstein, Jonathan Yaacov|Elazar, Assaf|Fleishman, Sarel Jacob', 'Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.|Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.|Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007318', '31461441', 'Membrane-protein design is an exciting and increasingly successful research area which has led to landmarks including the design of stable and accurate membrane-integral proteins based on coiled-coil motifs. Design of topologically more complex proteins, such as most receptors, channels, and transporters, however, demands an energy function that balances contributions from intra-protein contacts and protein-membrane interactions. Recent advances in water-soluble all-atom energy functions have increased the accuracy in structure-prediction benchmarks. The plasma membrane, however, imposes different physical constraints on protein solvation. To understand these constraints, we recently developed a high-throughput experimental screen, called dsTxcexb2L, and inferred apparent insertion energies for each amino acid at dozens of positions across the bacterial plasma membrane. Here, we express these profiles as lipophilicity energy terms in Rosetta and demonstrate that the new energy function outperforms previous ones in modelling and design benchmarks. Rosetta ab initio simulations starting from an extended chain recapitulate two-thirds of the experimentally determined structures of membrane-spanning homo-oligomers with <2.5xc3x85 root-mean-square deviation within the top-predicted five models (available online: http://tmhop.weizmann.ac.il). Furthermore, in two sequence-design benchmarks, the energy function improves discrimination of stabilizing point mutations and recapitulates natural membrane-protein sequences of known structure, thereby recommending this new energy function for membrane-protein modelling and design.'),
(89892, 2019, 'plos', 'Tracking Pseudomonas aeruginosa transmissions due to environmental contamination after discharge in ICUs using mathematical models', 'Pham, Thi Mui|Kretzschmar, Mirjam|Bertrand, Xavier|Bootsma, Martin|COMBACTE-MAGNET Consortium', 'Julius Center for Health Sciences and Primary Care of the UMC Utrecht, Utrecht University, Utrecht, The Netherlands.|Julius Center for Health Sciences and Primary Care of the UMC Utrecht, Utrecht University, Utrecht, The Netherlands.|Hygiène Hospitalière, Centre Hospitalier Régional Universitaire, Besançon, France.|Julius Center for Health Sciences and Primary Care of the UMC Utrecht, Utrecht University, Utrecht, The Netherlands.|Julius Center for Health Sciences and Primary Care of the UMC Utrecht, Utrecht University, Utrecht, The Netherlands.', 'Netherlands|Netherlands|France|Netherlands|Netherlands', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1006697', '31461450', 'Pseudomonas aeruginosa (P. aeruginosa) is an important cause of healthcare-associated infections, particularly in immunocompromised patients. Understanding how this multi-drug resistant pathogen is transmitted within intensive care units (ICUs) is crucial for devising and evaluating successful control strategies. While it is known that moist environments serve as natural reservoirs for P. aeruginosa, there is little quantitative evidence regarding the contribution of environmental contamination to its transmission within ICUs. Previous studies on other nosocomial pathogens rely on deploying specific values for environmental parameters derived from costly and laborious genotyping. Using solely longitudinal surveillance data, we estimated the relative importance of P. aeruginosa transmission routes by exploiting the fact that different routes cause different pattern of fluctuations in the prevalence. We developed a mathematical model including background transmission, cross-transmission and environmental contamination. Patients contribute to a pool of pathogens by shedding bacteria to the environment. Natural decay and cleaning of the environment lead to a reduction of that pool. By assigning the bacterial load shed during an ICU stay to cross-transmission, we were able to disentangle environmental contamination during and after a patients stay. Based on a data-augmented Markov Chain Monte Carlo method the relative importance of the considered acquisition routes is determined for two ICUs of the University hospital in Besançon (France). We used information about the admission and discharge days, screening days and screening results of the ICU patients. Both background and cross-transmission play a significant role in the transmission process in both ICUs. In contrast, only about 1% of the total transmissions were due to environmental contamination after discharge. Based on longitudinal surveillance data, we conclude that cleaning improvement of the environment after discharge might have only a limited impact regarding the prevention of P.A. infections in the two considered ICUs of the University hospital in Besançon. Our model was developed for P. aeruginosa but can be easily applied to other pathogens as well.'),
(89893, 2019, 'plos', 'Measuring the impact of gene prediction on gene loss estimates in Eukaryotes by quantifying falsely inferred absences', 'Deutekom, Eva S|Vosseberg, Julian|van Dam, Teunis J P|Snel, Berend', 'Theoretical Biology and Bioinformatics, Department of Biology, Science faculty, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology and Bioinformatics, Department of Biology, Science faculty, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology and Bioinformatics, Department of Biology, Science faculty, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology and Bioinformatics, Department of Biology, Science faculty, Utrecht University, Utrecht, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007301', '31461468', 'In recent years it became clear that in eukaryotic genome evolution gene loss is prevalent over gene gain. However, the absence of genes in an annotated genome is not always equivalent to the loss of genes. Due to sequencing issues, or incorrect gene prediction, genes can be falsely inferred as absent. This implies that loss estimates are overestimated and, more generally, that falsely inferred absences impact genomic comparative studies. However, reliable estimates of how prevalent this issue is are lacking. Here we quantified the impact of gene prediction on gene loss estimates in eukaryotes by analysing 209 phylogenetically diverse eukaryotic organisms and comparing their predicted proteomes to that of their respective six-frame translated genomes. We observe that 4.61% of domains per species were falsely inferred to be absent for Pfam domains predicted to have been present in the last eukaryotic common ancestor. Between phylogenetically different categories this estimate varies substantially: for clade-specific loss (ancestral loss) we found 1.30% and for species-specific loss 16.88% to be falsely inferred as absent. For BUSCO 1-to-1 orthologous families, 18.30% were falsely inferred to be absent. Finally, we showed that falsely inferred absences indeed impact loss estimates, with the number of losses decreasing by 11.78%. Our work strengthens the increasing number of studies showing that gene loss is an important factor in eukaryotic genome evolution. However, while we demonstrate that on average inferring gene absences from predicted proteomes is reliable, caution is warranted when inferring species-specific absences.'),
(89894, 2019, 'plos', 'A benchmark of computational CRISPR-Cas9 guide design methods', 'Bradford, Jacob|Perrin, Dimitri', 'School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, Queensland, Australia.|School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, Queensland, Australia.', 'Australia|Australia', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1007274', '31465436', 'The popularity of CRISPR-based gene editing has resulted in an abundance of tools to design CRISPR-Cas9 guides. This is also driven by the fact that designing highly specific and efficient guides is a crucial, but not trivial, task in using CRISPR for gene editing. Here, we thoroughly analyse the performance of 18 design tools. They are evaluated based on runtime performance, compute requirements, and guides generated. To achieve this, we implemented a method for auditing system resources while a given tool executes, and tested each tool on datasets of increasing size, derived from the mouse genome. We found that only five tools had a computational performance that would allow them to analyse an entire genome in a reasonable time, and without exhausting computing resources. There was wide variation in the guides identified, with some tools reporting every possible guide while others filtered for predicted efficiency. Some tools also failed to exclude guides that would target multiple positions in the genome. We also considered two collections with over a thousand guides each, for which experimental data is available. There is a lot of variation in performance between the datasets, but the relative order of the tools is partially conserved. Importantly, the most striking result is a lack of consensus between the tools. Our results show that CRISPR-Cas9 guide design tools need further work in order to achieve rapid whole-genome analysis and that improvements in guide design will likely require combining multiple approaches.'),
(89895, 2019, 'plos', 'Anatomically accurate model of EMG during index finger flexion and abduction derived from diffusion tensor imaging', 'Pereira Botelho, Diego|Curran, Kathleen|Lowery, Madeleine M', 'School of Electrical and Electronic Engineering, University College Dublin, Belfield, Dublin, Ireland.|School of Medicine, University College Dublin, Belfield, Dublin, Ireland.|School of Electrical and Electronic Engineering, University College Dublin, Belfield, Dublin, Ireland.', 'Ireland|Ireland|Ireland', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007267', '31465437', 'This study presents a modelling framework in which information on muscle fiber direction and orientation during contraction is derived from diffusion tensor imaging (DTI) and incorporated in a computational model of the surface electromyographic (EMG) signal. The proposed model makes use of the principle of reciprocity to simultaneously calculate the electric potentials produced at the recording electrode by charges distributed along an arbitrary number of muscle fibers within the muscle, allowing for a computationally efficient evaluation of extracellular motor unit action potentials. The approach is applied to the complex architecture of the first dorsal interosseous (FDI) muscle of the hand to simulate EMG during index finger flexion and abduction. Using diffusion tensor imaging methods, the results show how muscle fiber orientation and curvature in this intrinsic hand muscle change during flexion and abduction. Incorporation of anatomically accurate muscle architecture and other hand tissue morphologies enables the model to capture variations in extracellular action potential waveform shape across the motor unit population and to predict experimentally observed differences in EMG signal features when switching from index finger abduction to flexion. The simulation results illustrate how structural and electrical properties of the tissues comprising the volume conductor, in combination with fiber direction and curvature, shape the detected action potentials. Using the model, the relative contribution of motor units of different sizes located throughout the muscle under both conditions is examined, yielding a prediction of the detection profile of the surface EMG electrode array over the muscle cross-section.'),
(89896, 2019, 'plos', 'The formation of preference in risky choice', 'Glickman, Moshe|Sharoni, Orian|Levy, Dino J|Niebur, Ernst|Stuphorn, Veit|Usher, Marius', 'The School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel.|The School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel.|Coller School of Management, Tel Aviv University, Tel Aviv, Israel.|Department of Neuroscience and Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Neuroscience and Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, Maryland, United States of America.|The School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel|Israel|United States|United States|Israel', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007201', '31465438', 'A key question in decision-making is how people integrate amounts and probabilities to form preferences between risky alternatives. Here we rely on the general principle of integration-to-boundary to develop several biologically plausible process models of risky-choice, which account for both choices and response-times. These models allowed us to contrast two influential competing theories: i) within-alternative evaluations, based on multiplicative interaction between amounts and probabilities, ii) within-attribute comparisons across alternatives. To constrain the preference formation process, we monitored eye-fixations during decisions between pairs of simple lotteries, designed to systematically span the decision-space. The behavioral results indicate that the participants eye-scanning patterns were associated with risk-preferences and expected-value maximization. Crucially, model comparisons showed that within-alternative process models decisively outperformed within-attribute ones, in accounting for choices and response-times. These findings elucidate the psychological processes underlying preference formation when making risky-choices, and suggest that compensatory, within-alternative integration is an adaptive mechanism employed in human decision-making.'),
(89897, 2019, 'plos', 'Non-trophic interactions strengthen the diversity-functioning relationship in an ecological bioenergetic network model', 'Miele, Vincent|Guill, Christian|Ramos-Jiliberto, Rodrigo|Kéfi, Sonia', 'Université de Lyon, F-69000 Lyon, Université Lyon 1, CNRS, UMR5558, Laboratoire de Biométrie et Biologie Évolutive, F-69622 Villeurbanne, France.|Institut für Biochemie und Biologie, Universität Potsdam, Potsdam, Germany.|GEMA Center for Genomics, Ecology & Environment, Faculty of Sciences, Universidad Mayor, Huechuraba, Santiago, Chile.|Institut des Sciences de lEvolution de Montpellier, CNRS, Université de Montpellier, IRD, EPHE, Montpellier, France.', 'France|Germany|Chile|France', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007269', '31465440', 'Ecological communities are undeniably diverse, both in terms of the species that compose them as well as the type of interactions that link species to each other. Despite this long recognition of the coexistence of multiple interaction types in nature, little is known about the consequences of this diversity for community functioning. In the ongoing context of global change and increasing species extinction rates, it seems crucial to improve our understanding of the drivers of the relationship between species diversity and ecosystem functioning. Here, using a multispecies dynamical model of ecological communities including various interaction types (e.g. competition for space, predator interference, recruitment facilitation in addition to feeding), we studied the role of the presence and the intensity of these interactions for species diversity, community functioning (biomass and production) and the relationship between diversity and functioning.Taken jointly, the diverse interactions have significant effects on species diversity, whose amplitude and sign depend on the type of interactions involved and their relative abundance. They however consistently increase the slope of the relationship between diversity and functioning, suggesting that species losses might have stronger effects on community functioning than expected when ignoring the diversity of interaction types and focusing on feeding interactions only.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89898, 2019, 'plos', 'Network analyses to quantify effects of host movement in multilevel disease transmission models using foot and mouth disease in Cameroon as a case study', 'Pomeroy, Laura W|Kim, Hyeyoung|Xiao, Ningchuan|Moritz, Mark|Garabed, Rebecca', 'Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, United States of America.|Department of Geography, The Ohio State University, Columbus, OH, United States of America.|Department of Geography, The Ohio State University, Columbus, OH, United States of America.|Department of Anthropology, The Ohio State University, Columbus, OH, United States of America.|Department of Veterinary Preventive Medicine, The Ohio State University, Columbus, OH, United States of America.', 'United States|United States|United States|United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007184', '31465448', 'The dynamics of infectious diseases are greatly influenced by the movement of both susceptible and infected hosts. To accurately represent disease dynamics among a mobile host population, detailed movement models have been coupled with disease transmission models. However, a number of different host movement models have been proposed, each with their own set of assumptions and results that differ from the other models. Here, we compare two movement models coupled to the same disease transmission model using network analyses. This application of network analysis allows us to evaluate the fit and accuracy of the movement model in a multilevel modeling framework with more detail than established statistical modeling fitting methods. We used data that detailed mobile pastoralists movements as input for 100 stochastic simulations of a Spatio-Temporal Movement (STM) model and 100 stochastic simulations of an Individual Movement Model (IMM). Both models represent dynamic movement and subsequent contacts. We generated networks in which nodes represent camps and edges represent the distance between camps. We simulated pathogen transmission over these networks and tested five network metrics-strength, betweenness centrality, three-step reach, density, and transitivity-to determine which could predict disease simulation outcomes and thereby be used to correlate model simulation results with disease transmission simulations. We found that strength, network density, and three-step reach of movement model results correlated with the final epidemic size of outbreak simulations. Betweenness centrality only weakly correlated for the IMM model. Transitivity only weakly correlated for the STM model and time-varying IMM model metrics. We conclude that movement models coupled with disease transmission models can affect disease transmission results and should be carefully considered and vetted when modeling pathogen spread in mobile host populations. Strength, network density, and three-step reach can be used to evaluate movement models before disease simulations to predict final outbreak sizes. These findings can contribute to the analysis of multilevel models across systems.'),
(89899, 2019, 'plos', 'Toxin production spontaneously becomes regulated by local cell density in evolving bacterial populations', 'Doekes, Hilje M|de Boer, Rob J|Hermsen, Rutger', 'Theoretical Biology, Department of Biology, Utrecht University, Utrecht, the Netherlands.|Theoretical Biology, Department of Biology, Utrecht University, Utrecht, the Netherlands.|Theoretical Biology, Department of Biology, Utrecht University, Utrecht, the Netherlands.', 'Netherlands|Netherlands|Netherlands', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1007333', '31469819', 'The production of anticompetitor toxins is widespread among bacteria. Because production of such toxins is costly, it is typically regulated. In particular, many toxins are produced only when the local cell density is high. It is unclear which selection pressures shaped the evolution of density-dependent regulation of toxin production. Here, we study the evolution of toxin production, resistance and the response to a cell-density cue in a model of an evolving bacterial population with spatial structure. We present results for two growth regimes: (i) an undisturbed, fixed habitat in which only small fluctuations of cell density occur, and (ii) a serial-transfer regime with large fluctuations in cell density. We find that density-dependent toxin production can evolve under both regimes. However, the selection pressures driving the evolution of regulation differ. In the fixed habitat, regulation evolves because it allows cells to produce toxin only when opportunities for reproduction are highly limited (because of a high local cell density), and the effective fitness costs of toxin production are hence low. Under serial transfers, regulation evolves because it allows cells to switch from a fast-growing non-toxic phenotype when colonising a new habitat, to a slower-growing competitive toxic phenotype when the cell density increases. Colonies of such regulating cells rapidly expand into unoccupied space because their edges consist of fast-growing, non-toxin-producing cells, but are also combative because cells at the interfaces with competing colonies do produce toxin. Because under the two growth regimes different types of regulation evolve, our results underscore the importance of growth conditions in the evolution of social behaviour in bacteria.'),
(89900, 2019, 'plos', 'Red blood cells stabilize flow in brain microvascular networks', 'Schmid, Franca|Barrett, Matthew J P|Obrist, Dominik|Weber, Bruno|Jenny, Patrick', 'Institute of Fluid Dynamics, ETH Zurich, Sonneggstrasse 3, Zurich, Switzerland.|Institute of Pharmacology and Toxicology, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland.|ARTORG Center for Biomedical Engineering Research, University of Bern, Murtenstrasse 50, Bern, Switzerland.|Institute of Pharmacology and Toxicology, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland.|Institute of Fluid Dynamics, ETH Zurich, Sonneggstrasse 3, Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007231', '31469820', 'Capillaries are the prime location for oxygen and nutrient exchange in all tissues. Despite their fundamental role, our knowledge of perfusion and flow regulation in cortical capillary beds is still limited. Here, we use in vivo measurements and blood flow simulations in anatomically accurate microvascular network to investigate the impact of red blood cells (RBCs) on microvascular flow. Based on these in vivo and in silico experiments, we show that the impact of RBCs leads to a bias toward equating the values of the outflow velocities at divergent capillary bifurcations, for which we coin the term well-balanced bifurcations. Our simulation results further reveal that hematocrit heterogeneity is directly caused by the RBC dynamics, i.e. by their unequal partitioning at bifurcations and their effect on vessel resistance. These results provide the first in vivo evidence of the impact of RBC dynamics on the flow field in the cortical microvasculature. By structural and functional analyses of our blood flow simulations we show that capillary diameter changes locally alter flow and RBC distribution. A dilation of 10% along a vessel length of 100 xcexbcm increases the flow on average by 21% in the dilated vessel downstream a well-balanced bifurcation. The number of RBCs rises on average by 27%. Importantly, RBC up-regulation proves to be more effective the more balanced the outflow velocities at the upstream bifurcation are. Taken together, we conclude that diameter changes at capillary level bear potential to locally change the flow field and the RBC distribution. Moreover, our results suggest that the balancing of outflow velocities contributes to the robustness of perfusion. Based on our in silico results, we anticipate that the bi-phasic nature of blood and small-scale regulations are essential for a well-adjusted oxygen and energy substrate supply.'),
(89901, 2019, 'plos', 'Mechanical properties of tubulin intra- and inter-dimer interfaces and their implications for microtubule dynamic instability', 'Fedorov, Vladimir A|Orekhov, Philipp S|Kholina, Ekaterina G|Zhmurov, Artem A|Ataullakhanov, Fazoil I|Kovalenko, Ilya B|Gudimchuk, Nikita B', 'Department of Biology, Lomonosov Moscow State University, Moscow, Russia.|Department of Biology, Lomonosov Moscow State University, Moscow, Russia.|Department of Biology, Lomonosov Moscow State University, Moscow, Russia.|Moscow Institute of Physics and Technology, Dolgoprudny, Russia.|Moscow Institute of Physics and Technology, Dolgoprudny, Russia.|Department of Biology, Lomonosov Moscow State University, Moscow, Russia.|Department of Physics, Lomonosov Moscow State University, Moscow, Russia.', '-|-|-|-|-|-|-', 5, '-', 'Journal Article', '10.1371/journal.pcbi.1007327', '31469822', 'Thirteen tubulin protofilaments, made of xcexb1xcexb2-tubulin heterodimers, interact laterally to produce cytoskeletal microtubules. Microtubules exhibit the striking property of dynamic instability, manifested in their intermittent growth and shrinkage at both ends. This behavior is key to many cellular processes, such as cell division, migration, maintenance of cell shape, etc. Although assembly and disassembly of microtubules is known to be linked to hydrolysis of a guanosine triphosphate molecule in the pocket of xcexb2-tubulin, detailed mechanistic understanding of corresponding conformational changes is still lacking. Here we take advantage of the recent generation of in-microtubule structures of tubulin to examine the properties of protofilaments, which serve as important microtubule assembly and disassembly intermediates. We find that initially straight tubulin protofilaments, relax to similar non-radially curved and slightly twisted conformations. Our analysis further suggests that guanosine triphosphate hydrolysis primarily affects the flexibility and conformation of the inter-dimer interface, without a strong impact on the shape or flexibility of xcexb1xcexb2-heterodimer. Inter-dimer interfaces are significantly more flexible compared to intra-dimer interfaces. We argue that such a difference in flexibility could be key for distinct stability of the plus and minus microtubule ends. The higher flexibility of the inter-dimer interface may have implications for development of pulling force by curving tubulin protofilaments during microtubule disassembly, a process of major importance for chromosome motions in mitosis.'),
(89902, 2019, 'plos', 'PanoView: An iterative clustering method for single-cell RNA sequencing data', 'Hu, Ming-Wen|Kim, Dong Won|Liu, Sheng|Zack, Donald J|Blackshaw, Seth|Qian, Jiang', 'Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.|Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.|Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.|Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.|Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.|Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.', 'United States|United States|United States|United States|United States|United States', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007040', '31469823', 'Single-cell RNA-sequencing (scRNA-seq) provides new opportunities to gain a mechanistic understanding of many biological processes. Current approaches for single cell clustering are often sensitive to the input parameters and have difficulty dealing with cell types with different densities. Here, we present Panoramic View (PanoView), an iterative method integrated with a novel density-based clustering, Ordering Local Maximum by Convex hull (OLMC), that uses a heuristic approach to estimate the required parameters based on the input data structures. In each iteration, PanoView will identify the most confident cell clusters and repeat the clustering with the remaining cells in a new PCA space. Without adjusting any parameter in PanoView, we demonstrated that PanoView was able to detect major and rare cell types simultaneously and outperformed other existing methods in both simulated datasets and published single-cell RNA-sequencing datasets. Finally, we conducted scRNA-Seq analysis of embryonic mouse hypothalamus, and PanoView was able to reveal known cell types and several rare cell subpopulations.'),
(89903, 2019, 'plos', 'Effects of persistent sodium current blockade in respiratory circuits depend on the pharmacological mechanism of action and network dynamics', 'Phillips, Ryan S|Rubin, Jonathan E', 'Department of Mathematics and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Mathematics and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006938', '31469828', 'The mechanism(s) of action of most commonly used pharmacological blockers of voltage-gated ion channels are well understood, however, this knowledge is rarely considered when interpreting experimental data. Effects of blockade are often assumed to be equivalent, regardless of the mechanism of the blocker involved. Using computer simulations, we demonstrate that this assumption may not always be correct. We simulate the blockade of a persistent sodium current (INaP), proposed to underlie rhythm generation in pre-Bötzinger complex (pre-BötC) respiratory neurons, via two distinct pharmacological mechanisms: (1) pore obstruction mediated by tetrodotoxin and (2) altered inactivation dynamics mediated by riluzole. The reported effects of experimental application of tetrodotoxin and riluzole in respiratory circuits are diverse and seemingly contradictory and have led to considerable debate within the field as to the specific role of INaP in respiratory circuits. The results of our simulations match a wide array of experimental data spanning from the level of isolated pre-BötC neurons to the level of the intact respiratory network and also generate a series of experimentally testable predictions. Specifically, in this study we: (1) provide a mechanistic explanation for seemingly contradictory experimental results from in vitro studies of INaP block, (2) show that the effects of INaP block in in vitro preparations are not necessarily equivalent to those in more intact preparations, (3) demonstrate and explain why riluzole application may fail to effectively block INaP in the intact respiratory network, and (4) derive the prediction that effective block of INaP by low concentration tetrodotoxin will stop respiratory rhythm generation in the intact respiratory network. These simulations support a critical role for INaP in respiratory rhythmogenesis in vivo and illustrate the importance of considering mechanism when interpreting and simulating data relating to pharmacological blockade.'),
(89904, 2019, 'plos', 'Dark-matter matters: Discriminating subtle blood cancers using the darkest DNA', 'Parida, Laxmi|Haferlach, Claudia|Rhrissorrakrai, Kahn|Utro, Filippo|Levovitz, Chaya|Kern, Wolfgang|Nadarajah, Niroshan|Twardziok, Sven|Hutter, Stephan|Meggendorfer, Manja|Walter, Wencke|Baer, Constance|Haferlach, Torsten', 'IBM Research, Yorktown Heights, New York, United States of America.|MLL Munich Leukemia Laboratory, Munich, Germany.|IBM Research, Yorktown Heights, New York, United States of America.|IBM Research, Yorktown Heights, New York, United States of America.|IBM Research, Yorktown Heights, New York, United States of America.|MLL Munich Leukemia Laboratory, Munich, Germany.|MLL Munich Leukemia Laboratory, Munich, Germany.|MLL Munich Leukemia Laboratory, Munich, Germany.|MLL Munich Leukemia Laboratory, Munich, Germany.|MLL Munich Leukemia Laboratory, Munich, Germany.|MLL Munich Leukemia Laboratory, Munich, Germany.|MLL Munich Leukemia Laboratory, Munich, Germany.|MLL Munich Leukemia Laboratory, Munich, Germany.', 'United States|Germany|United States|United States|United States|Germany|Germany|Germany|Germany|Germ', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007332', '31469830', 'The confluence of deep sequencing and powerful machine learning is providing an unprecedented peek at the darkest of the dark genomic matter, the non-coding genomic regions lacking any functional annotation. While deep sequencing uncovers rare tumor variants, the heterogeneity of the disease confounds the best of machine learning (ML) algorithms. Here we set out to answer if the dark-matter of the genome encompass signals that can distinguish the fine subtypes of disease that are otherwise genomically indistinguishable. We introduce a novel stochastic regularization, ReVeaL, that empowers ML to discriminate subtle cancer subtypes even from the same cell of origin. Analogous to heritability, implicitly defined on whole genome, we use predictability (F1 score) definable on portions of the genome. In an effort to distinguish cancer subtypes using dark-matter DNA, we applied ReVeaL to a new WGS dataset from 727 patient samples with seven forms of hematological cancers and assessed the predictivity over several genomic regions including genic, non-dark, non-coding, non-genic, and dark. ReVeaL enabled improved discrimination of cancer subtypes for all segments of the genome. The non-genic, non-coding and dark-matter had the highest F1 scores, with dark-matter having the highest level of predictability. Based on ReVeaLs predictability of different genomic regions, dark-matter contains enough signal to significantly discriminate fine subtypes of disease. Hence, the agglomeration of rare variants, even in the hitherto unannotated and ill-understood regions of the genome, may play a substantial role in the disease etiology and deserve much more attention.'),
(89905, 2019, 'plos', 'Fast uncertainty quantification for dynamic flux balance analysis using non-smooth polynomial chaos expansions', 'Paulson, Joel A|Martin-Casas, Marc|Mesbah, Ali', 'Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, California, United States of America.|Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, California, United States of America.|Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, California, United States of America.', 'United States|United States|United States', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007308', '31469832', 'We present a novel surrogate modeling method that can be used to accelerate the solution of uncertainty quantification (UQ) problems arising in nonlinear and non-smooth models of biological systems. In particular, we focus on dynamic flux balance analysis (DFBA) models that couple intracellular fluxes, found from the solution of a constrained metabolic network model of the cellular metabolism, to the time-varying nature of the extracellular substrate and product concentrations. DFBA models are generally computationally expensive and present unique challenges to UQ, as they entail dynamic simulations with discrete events that correspond to switches in the active set of the solution of the constrained intracellular model. The proposed non-smooth polynomial chaos expansion (nsPCE) method is an extension of traditional PCE that can effectively capture singularities in the DFBA model response due to the occurrence of these discrete events. The key idea in nsPCE is to use a model of the singularity time to partition the parameter space into two elements on which the model response behaves smoothly. Separate PCE models are then fit in both elements using a basis-adaptive sparse regression approach that is known to scale well with respect to the number of uncertain parameters. We demonstrate the effectiveness of nsPCE on a DFBA model of an E. coli monoculture that consists of 1075 reactions and 761 metabolites. We first illustrate how traditional PCE is unable to handle problems of this level of complexity. We demonstrate that over 800-fold savings in computational cost of uncertainty propagation and Bayesian estimation of parameters in the substrate uptake kinetics can be achieved by using the nsPCE surrogates in place of the full DFBA model simulations. We then investigate the scalability of the nsPCE method by utilizing it for global sensitivity analysis and maximum a posteriori estimation in a synthetic metabolic network problem with a larger number of parameters related to both intracellular and extracellular quantities.'),
(89906, 2019, 'plos', 'Benchmarking network propagation methods for disease gene identification', 'Picart-Armada, Sergio|Barrett, Steven J|Willé, David R|Perera-Lluna, Alexandre|Gutteridge, Alex|Dessailly, Benoit H', 'B2SLab, Departament dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, CIBER-BBN, Barcelona, Spain.|Research Statistics, GSK, Stevenage, United Kingdom.|Research Statistics, GSK, Stevenage, United Kingdom.|B2SLab, Departament dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, CIBER-BBN, Barcelona, Spain.|Computational Biology and Statistics, GSK, Stevenage, United Kingdom.|GSK Vaccines, Rixensart, Belgium.', 'Spain|United Kingdom|United Kingdom|Spain|United Kingdom|Belgium', 6, '-', 'Journal Article', '10.1371/journal.pcbi.1007276', '31479437', 'In-silico identification of potential target genes for disease is an essential aspect of drug target discovery. Recent studies suggest that successful targets can be found through by leveraging genetic, genomic and protein interaction information. Here, we systematically tested the ability of 12 varied algorithms, based on network propagation, to identify genes that have been targeted by any drug, on gene-disease data from 22 common non-cancerous diseases in OpenTargets. We considered two biological networks, six performance metrics and compared two types of input gene-disease association scores. The impact of the design factors in performance was quantified through additive explanatory models. Standard cross-validation led to over-optimistic performance estimates due to the presence of protein complexes. In order to obtain realistic estimates, we introduced two novel protein complex-aware cross-validation schemes. When seeding biological networks with known drug targets, machine learning and diffusion-based methods found around 2-4 true targets within the top 20 suggestions. Seeding the networks with genes associated to disease by genetics decreased performance below 1 true hit on average. The use of a larger network, although noisier, improved overall performance. We conclude that diffusion-based prioritisers and machine learning applied to diffusion-based features are suited for drug discovery in practice and improve over simpler neighbour-voting methods. We also demonstrate the large impact of choosing an adequate validation strategy and the definition of seed disease genes.'),
(89907, 2019, 'plos', 'Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting', 'Lu, Alex X|Kraus, Oren Z|Cooper, Sam|Moses, Alan M', 'Department of Computer Science, University of Toronto, Toronto, Canada.|Phenomic AI, Toronto, Canada.|Phenomic AI, Toronto, Canada.|Department of Computer Science, University of Toronto, Toronto, Canada.', 'Canada|Canada|Canada|Canada', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007348', '31479439', 'Cellular microscopy images contain rich insights about biology. To extract this information, researchers use features, or measurements of the patterns of interest in the images. Here, we introduce a convolutional neural network (CNN) to automatically design features for fluorescence microscopy. We use a self-supervised method to learn feature representations of single cells in microscopy images without labelled training data. We train CNNs on a simple task that leverages the inherent structure of microscopy images and controls for variation in cell morphology and imaging: given one cell from an image, the CNN is asked to predict the fluorescence pattern in a second different cell from the same image. We show that our method learns high-quality features that describe protein expression patterns in single cells both yeast and human microscopy datasets. Moreover, we demonstrate that our features are useful for exploratory biological analysis, by capturing high-resolution cellular components in a proteome-wide cluster analysis of human proteins, and by quantifying multi-localized proteins and single-cell variability. We believe paired cell inpainting is a generalizable method to obtain feature representations of single cells in multichannel microscopy images.'),
(89908, 2019, 'plos', 'Deconvolving multiplexed protease signatures with substrate reduction and activity clustering', 'Zhuang, Qinwei|Holt, Brandon Alexander|Kwong, Gabriel A|Qiu, Peng', 'School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech College of Engineering and Emory School of Medicine, Atlanta, Georgia, United States of America.|Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech College of Engineering and Emory School of Medicine, Atlanta, Georgia, United States of America.|Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech College of Engineering and Emory School of Medicine, Atlanta, Georgia, United States of America.', 'Georgia|Georgia|Georgia|Georgia', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006909', '31479443', 'Proteases are multifunctional, promiscuous enzymes that degrade proteins as well as peptides and drive important processes in health and disease. Current technology has enabled the construction of libraries of peptide substrates that detect protease activity, which provides valuable biological information. An ideal library would be orthogonal, such that each protease only hydrolyzes one unique substrate, however this is impractical due to off-target promiscuity (i.e., one protease targets multiple different substrates). Therefore, when a library of probes is exposed to a cocktail of proteases, each protease activates multiple probes, producing a convoluted signature. Computational methods for parsing these signatures to estimate individual protease activities primarily use an extensive collection of all possible protease-substrate combinations, which require impractical amounts of training data when expanding to search for more candidate substrates. Here we provide a computational method for estimating protease activities efficiently by reducing the number of substrates and clustering proteases with similar cleavage activities into families. We envision that this method will be used to extract meaningful diagnostic information from biological samples.'),
(89909, 2019, 'plos', 'The FACTS model of speech motor control: Fusing state estimation and task-based control', 'Parrell, Benjamin|Ramanarayanan, Vikram|Nagarajan, Srikantan|Houde, John', 'Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Department of Otolaryngology - Head and Neck Surgery, University of California, San Francisco, San Francisco, California, United States of America.|Department of Otolaryngology - Head and Neck Surgery, University of California, San Francisco, San Francisco, California, United States of America.|Department of Otolaryngology - Head and Neck Surgery, University of California, San Francisco, San Francisco, California, United States of America.', 'United States|United States|United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007321', '31479444', 'We present a new computational model of speech motor control: the Feedback-Aware Control of Tasks in Speech or FACTS model. FACTS employs a hierarchical state feedback control architecture to control simulated vocal tract and produce intelligible speech. The model includes higher-level control of speech tasks and lower-level control of speech articulators. The task controller is modeled as a dynamical system governing the creation of desired constrictions in the vocal tract, after Task Dynamics. Both the task and articulatory controllers rely on an internal estimate of the current state of the vocal tract to generate motor commands. This estimate is derived, based on efference copy of applied controls, from a forward model that predicts both the next vocal tract state as well as expected auditory and somatosensory feedback. A comparison between predicted feedback and actual feedback is then used to update the internal state prediction. FACTS is able to qualitatively replicate many characteristics of the human speech system: the model is robust to noise in both the sensory and motor pathways, is relatively unaffected by a loss of auditory feedback but is more significantly impacted by the loss of somatosensory feedback, and responds appropriately to externally-imposed alterations of auditory and somatosensory feedback. The model also replicates previously hypothesized trade-offs between reliance on auditory and somatosensory feedback and shows for the first time how this relationship may be mediated by acuity in each sensory domain. These results have important implications for our understanding of the speech motor control system in humans.'),
(89910, 2019, 'plos', 'Executable pathway analysis using ensemble discrete-state modeling for large-scale data', 'Palli, Rohith|Palshikar, Mukta G|Thakar, Juilee', 'Medical Scientist Training Program, University of Rochester, Rochester, New York, United States of America.|Biophysics, Structural, and Computational Biology Program, University of Rochester, Rochester, New York, United States of America.|Biophysics, Structural, and Computational Biology Program, University of Rochester, Rochester, New York, United States of America.', 'United States|United States|United States', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007317', '31479446', 'Pathway analysis is widely used to gain mechanistic insights from high-throughput omics data. However, most existing methods do not consider signal integration represented by pathway topology, resulting in enrichment of convergent pathways when downstream genes are modulated. Incorporation of signal flow and integration in pathway analysis could rank the pathways based on modulation in key regulatory genes. This implementation can be facilitated for large-scale data by discrete state network modeling due to simplicity in parameterization. Here, we model cellular heterogeneity using discrete state dynamics and measure pathway activities in cross-sectional data. We introduce a new algorithm, Boolean Omics Network Invariant-Time Analysis (BONITA), for signal propagation, signal integration, and pathway analysis. Our signal propagation approach models heterogeneity in transcriptomic data as arising from intercellular heterogeneity rather than intracellular stochasticity, and propagates binary signals repeatedly across networks. Logic rules defining signal integration are inferred by genetic algorithm and are refined by local search. The rules determine the impact of each node in a pathway, which is used to score the probability of the pathways modulation by chance. We have comprehensively tested BONITA for application to transcriptomics data from translational studies. Comparison with state-of-the-art pathway analysis methods shows that BONITA has higher sensitivity at lower levels of source node modulation and similar sensitivity at higher levels of source node modulation. Application of BONITA pathway analysis to previously validated RNA-sequencing studies identifies additional relevant pathways in in-vitro human cell line experiments and in-vivo infant studies. Additionally, BONITA successfully detected modulation of disease specific pathways when comparing relevant RNA-sequencing data with healthy controls. Most interestingly, the two highest impact score nodes identified by BONITA included known drug targets. Thus, BONITA is a powerful approach to prioritize not only pathways but also specific mechanistic role of genes compared to existing methods. BONITA is available at: https://github.com/thakar-lab/BONITA.'),
(89911, 2019, 'plos', 'Estimating information in time-varying signals', 'Cepeda-Humerez, Sarah Anhala|Ruess, Jakob|Tkaxc4x8dik, Gaxc5xa1per', 'Institute of Science and Technology Austria, A-3400 Klosterneuburg, Austria.|Inria Saclay - Ile-de-France, F-91120 Palaiseau, France.|Institute of Science and Technology Austria, A-3400 Klosterneuburg, Austria.', 'Austria|France|Austria', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1007290', '31479447', 'Across diverse biological systems-ranging from neural networks to intracellular signaling and genetic regulatory networks-the information about changes in the environment is frequently encoded in the full temporal dynamics of the network nodes. A pressing data-analysis challenge has thus been to efficiently estimate the amount of information that these dynamics convey from experimental data. Here we develop and evaluate decoding-based estimation methods to lower bound the mutual information about a finite set of inputs, encoded in single-cell high-dimensional time series data. For biological reaction networks governed by the chemical Master equation, we derive model-based information approximations and analytical upper bounds, against which we benchmark our proposed model-free decoding estimators. In contrast to the frequently-used k-nearest-neighbor estimator, decoding-based estimators robustly extract a large fraction of the available information from high-dimensional trajectories with a realistic number of data samples. We apply these estimators to previously published data on Erk and Ca2+ signaling in mammalian cells and to yeast stress-response, and find that substantial amount of information about environmental state can be encoded by non-trivial response statistics even in stationary signals. We argue that these single-cell, decoding-based information estimates, rather than the commonly-used tests for significant differences between selected population response statistics, provide a proper and unbiased measure for the performance of biological signaling networks.'),
(89912, 2019, 'plos', 'Evaluation of parameters affecting performance and reliability of machine learning-based antibiotic susceptibility testing from whole genome sequencing data', 'Hicks, Allison L|Wheeler, Nicole|Sánchez-Busó, Leonor|Rakeman, Jennifer L|Harris, Simon R|Grad, Yonatan H', 'Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom.|Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom.|Public Health Laboratory, Division of Disease Control, New York City Department of Health and Mental Hygiene, New York, New York, United States of America.|Microbiotica Ltd, Biodata Innovation Centre, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom.|Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.', 'United States|United Kingdom|United Kingdom|United States|United Kingdom|United States', 7, '-', 'Journal Article', '10.1371/journal.pcbi.1007349', '31479500', 'Prediction of antibiotic resistance phenotypes from whole genome sequencing data by machine learning methods has been proposed as a promising platform for the development of sequence-based diagnostics. However, there has been no systematic evaluation of factors that may influence performance of such models, how they might apply to and vary across clinical populations, and what the implications might be in the clinical setting. Here, we performed a meta-analysis of seven large Neisseria gonorrhoeae datasets, as well as Klebsiella pneumoniae and Acinetobacter baumannii datasets, with whole genome sequence data and antibiotic susceptibility phenotypes using set covering machine classification, random forest classification, and random forest regression models to predict resistance phenotypes from genotype. We demonstrate how model performance varies by drug, dataset, resistance metric, and species, reflecting the complexities of generating clinically relevant conclusions from machine learning-derived models. Our findings underscore the importance of incorporating relevant biological and epidemiological knowledge into model design and assessment and suggest that doing so can inform tailored modeling for individual drugs, pathogens, and clinical populations. We further suggest that continued comprehensive sampling and incorporation of up-to-date whole genome sequence data, resistance phenotypes, and treatment outcome data into model training will be crucial to the clinical utility and sustainability of machine learning-based molecular diagnostics.'),
(89913, 2019, 'plos', 'Integrating thermodynamic and sequence contexts improves protein-RNA binding prediction', 'Su, Yufeng|Luo, Yunan|Zhao, Xiaoming|Liu, Yang|Peng, Jian', 'Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.', 'United States|United States|United States|United States|United States', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1007283', '31483777', 'Predicting RNA-binding protein (RBP) specificity is important for understanding gene expression regulation and RNA-mediated enzymatic processes. It is widely believed that RBP binding specificity is determined by both the sequence and structural contexts of RNAs. Existing approaches, including traditional machine learning algorithms and more recently, deep learning models, have been extensively applied to integrate RNA sequence and its predicted or experimental RNA structural probabilities for improving the accuracy of RBP binding prediction. Such models were trained mostly on the large-scale in vitro datasets, such as the RNAcompete dataset. However, in RNAcompete, most synthetic RNAs are unstructured, which makes machine learning methods not effectively extract RBP-binding structural preferences. Furthermore, RNA structure may be variable or multi-modal according to both theoretical and experimental evidence. In this work, we propose ThermoNet, a thermodynamic prediction model by integrating a new sequence-embedding convolutional neural network model over a thermodynamic ensemble of RNA secondary structures. First, the sequence-embedding convolutional neural network generalizes the existing k-mer based methods by jointly learning convolutional filters and k-mer embeddings to represent RNA sequence contexts. Second, the thermodynamic average of deep-learning predictions is able to explore structural variability and improves the prediction, especially for the structured RNAs. Extensive experiments demonstrate that our method significantly outperforms existing approaches, including RCK, DeepBind and several other recent state-of-the-art methods for predictions on both in vitro and in vivo data. The implementation of ThermoNet is available at https://github.com/suyufeng/ThermoNet.'),
(89914, 2019, 'plos', '3D computational models explain muscle activation patterns and energetic functions of internal structures in fish swimming', 'Ming, Tingyu|Jin, Bowen|Song, Jialei|Luo, Haoxiang|Du, Ruxu|Ding, Yang', 'Beijing Computational Science Research Center, Haidian District, Beijing, China.|Beijing Computational Science Research Center, Haidian District, Beijing, China.|Beijing Computational Science Research Center, Haidian District, Beijing, China.|Department of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America.|Department of Mechanical and Automation Engineering, Chinese University of Hong Kong, Hong Kong SAR, China.|Beijing Computational Science Research Center, Haidian District, Beijing, China.', 'China|China|China|United States|China|China', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006883', '31487282', 'How muscles are used is a key to understanding the internal driving of fish swimming. However, the underlying mechanisms of some features of the muscle activation patterns and their differential appearance in different species are still obscure. In this study, we explain the muscle activation patterns by using 3D computational fluid dynamics models coupled to the motion of fish with prescribed deformation and examining the torque and power required along the fish body with two primary swimming modes. We find that the torque required by the hydrodynamic forces and body inertia exhibits a wave pattern that travels faster than the curvature wave in both anguilliform and carangiform swimmers, which can explain the traveling wave speeds of the muscle activations. Notably, intermittent negative power (i.e., power delivered by the fluid to the body) on the posterior part, along with a timely transfer of torque and energy by tendons, explains the decrease in the duration of muscle activation towards the tail. The torque contribution from the body elasticity further clarifies the wave speed increase or the reverse of the wave direction of the muscle activation on the posterior part of a carangiform swimmer. For anguilliform swimmers, the absence of the aforementioned changes in the muscle activation on the posterior part is consistent with our torque prediction and the absence of long tendons from experimental observations. These results provide novel insights into the functions of muscles and tendons as an integral part of the internal driving system, especially from an energy perspective, and they highlight the differences in the internal driving systems between the two primary swimming modes.'),
(89915, 2019, 'plos', 'p13CMFA: Parsimonious 13C metabolic flux analysis', 'Foguet, Carles|Jayaraman, Anusha|Marin, Silvia|Selivanov, Vitaly A|Moreno, Pablo|Messeguer, Ramon|de Atauri, Pedro|Cascante, Marta', 'Department of Biochemistry and Molecular Biomedicine & Institute of Biomedicine of University of Barcelona, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|Department of Biochemistry and Molecular Biomedicine & Institute of Biomedicine of University of Barcelona, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|Department of Biochemistry and Molecular Biomedicine & Institute of Biomedicine of University of Barcelona, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|Department of Biochemistry and Molecular Biomedicine & Institute of Biomedicine of University of Barcelona, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom.|LEITAT Technological Center, Health & Biomedicine Unit, Barcelona, Spain.|Department of Biochemistry and Molecular Biomedicine & Institute of Biomedicine of University of Barcelona, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|Department of Biochemistry and Molecular Biomedicine & Institute of Biomedicine of University of Barcelona, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.', 'Spain|Spain|Spain|Spain|United Kingdom|Spain|Spain|Spain', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007310', '31490922', 'Deciphering the mechanisms of regulation of metabolic networks subjected to perturbations, including disease states and drug-induced stress, relies on tracing metabolic fluxes. One of the most informative data to predict metabolic fluxes are 13C based metabolomics, which provide information about how carbons are redistributed along central carbon metabolism. Such data can be integrated using 13C Metabolic Flux Analysis (13C MFA) to provide quantitative metabolic maps of flux distributions. However, 13C MFA might be unable to reduce the solution space towards a unique solution either in large metabolic networks or when small sets of measurements are integrated. Here we present parsimonious 13C MFA (p13CMFA), an approach that runs a secondary optimization in the 13C MFA solution space to identify the solution that minimizes the total reaction flux. Furthermore, flux minimization can be weighted by gene expression measurements allowing seamless integration of gene expression data with 13C data. As proof of concept, we demonstrate how p13CMFA can be used to estimate intracellular flux distributions from 13C measurements and transcriptomics data. We have implemented p13CMFA in Iso2Flux, our in-house developed isotopic steady-state 13C MFA software. The source code is freely available on GitHub (https://github.com/cfoguet/iso2flux/releases/tag/0.7.2).'),
(89916, 2019, 'plos', 'Learning the structure of the world: The adaptive nature of state-space and action representations in multi-stage decision-making', 'Dezfouli, Amir|Balleine, Bernard W', 'School of Psychology, UNSW, Sydney, Australia.|School of Psychology, UNSW, Sydney, Australia.', 'Australia|Australia', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007334', '31490932', 'State-space and action representations form the building blocks of decision-making processes in the brain, states map external cues to the current situation of the agent whereas actions provide the set of motor commands from which the agent can choose to achieve specific goals. Although these factors differ across environments, it is currently unknown whether or how accurately state and action representations are acquired by the agent because previous experiments have typically provided this information a priori through instruction or pre-training. Here we studied how state and action representations adapt to reflect the structure of the world when such a priori knowledge is not available. We used a sequential decision-making task in rats in which they were required to pass through multiple states before reaching the goal, and for which the number of states and how they map onto external cues were unknown a priori. We found that, early in training, animals selected actions as if the task was not sequential and outcomes were the immediate consequence of the most proximal action. During the course of training, however, rats recovered the true structure of the environment and made decisions based on the expanded state-space, reflecting the multiple stages of the task. Similarly, we found that the set of actions expanded with training, although the emergence of new action sequences was sensitive to the experimental parameters and specifics of the training procedure. We conclude that the profile of choices shows a gradual shift from simple representations to more complex structures compatible with the structure of the world.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89917, 2019, 'plos', 'Cost-benefit trade-offs in decision-making and learning', 'Sidarus, Nura|Palminteri, Stefano|Chambon, Valérian', 'Institut Jean Nicod, Département dÉtudes Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France.|Laboratoire de Neurosciences Cognitives Computationnelles, Département dÉtudes Cognitives, École Normale Supérieure, INSERM, PSL University, Paris, France.|Institut Jean Nicod, Département dÉtudes Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France.', 'France|France|France', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007326', '31490934', 'Value-based decision-making involves trading off the cost associated with an action against its expected reward. Research has shown that both physical and mental effort constitute such subjective costs, biasing choices away from effortful actions, and discounting the value of obtained rewards. Facing conflicts between competing action alternatives is considered aversive, as recruiting cognitive control to overcome conflict is effortful. Moreover, engaging control to proactively suppress irrelevant information that could conflict with task-relevant information would presumably also be cognitively costly. Yet, it remains unclear whether the cognitive control demands involved in preventing and resolving conflict also constitute costs in value-based decisions. The present study investigated this question by embedding irrelevant distractors (flanker arrows) within a reversal-learning task, with intermixed free and instructed trials. Results showed that participants learned to adapt their free choices to maximize rewards, but were nevertheless biased to follow the suggestions of irrelevant distractors. Thus, the perceived cost of investing cognitive control to suppress an external suggestion could sometimes trump internal value representations. By adapting computational models of reinforcement learning, we assessed the influence of conflict at both the decision and learning stages. Modelling the decision showed that free choices were more biased when participants were less sure about which action was more rewarding. This supports the hypothesis that the costs linked to conflict management were traded off against expected rewards. During the learning phase, we found that learning rates were reduced in instructed, relative to free, choices. Learning rates were further reduced by conflict between an instruction and subjective action values, whereas learning was not robustly influenced by conflict between ones actions and external distractors. Our results show that the subjective cognitive control costs linked to conflict factor into value-based decision-making, and highlight that different types of conflict may have different effects on learning about action outcomes.'),
(89918, 2019, 'plos', 'Designing combination therapies with modeling chaperoned machine learning', 'Zhang, Yin|Huynh, Julie M|Liu, Guan-Sheng|Ballweg, Richard|Aryeh, Kayenat S|Paek, Andrew L|Zhang, Tongli', 'Division of Biostatistics and Epidemiology, Cincinnati Childrens Hospital Medical Center, Cincinnati, Ohio, United States of America.|Molecular and Cellular Biology, University of Arizona, Tucson, United States of America.|Department of Pharmacology and Systems Physiology, College of Medicine, University of Cincinnati, Cincinnati, Ohio, United States of America.|Department of Pharmacology and Systems Physiology, College of Medicine, University of Cincinnati, Cincinnati, Ohio, United States of America.|Molecular and Cellular Biology, University of Arizona, Tucson, United States of America.|Molecular and Cellular Biology, University of Arizona, Tucson, United States of America.|Department of Pharmacology and Systems Physiology, College of Medicine, University of Cincinnati, Cincinnati, Ohio, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007158', '31498788', 'Chemotherapy resistance is a major challenge to the effective treatment of cancer. Thus, a systematic pipeline for the efficient identification of effective combination treatments could bring huge biomedical benefit. In order to facilitate rational design of combination therapies, we developed a comprehensive computational model that incorporates the available biological knowledge and relevant experimental data on the life-and-death response of individual cancer cells to cisplatin or cisplatin combined with the TNF-related apoptosis-inducing ligand (TRAIL). The models predictions, that a combination treatment of cisplatin and TRAIL would enhance cancer cell death and exhibit a two-wave killing temporal pattern, was validated by measuring the dynamics of p53 accumulation, cell fate, and cell death in single cells. The validated model was then subjected to a systematic analysis with an ensemble of diverse machine learning methods. Though each method is characterized by a different algorithm, they collectively identified several molecular players that can sensitize tumor cells to cisplatin-induced apoptosis (sensitizers). The identified sensitizers are consistent with previous experimental observations. Overall, we have illustrated that machine learning analysis of an experimentally validated mechanistic model can convert our available knowledge into the identity of biologically meaningful sensitizers. This knowledge can then be leveraged to design treatment strategies that could improve the efficacy of chemotherapy.'),
(89919, 2019, 'plos', 'Prepaid parameter estimation without likelihoods', 'Mestdagh, Merijn|Verdonck, Stijn|Meers, Kristof|Loossens, Tim|Tuerlinckx, Francis', 'KU Leuven, University of Leuven, Leuven, Belgium.|KU Leuven, University of Leuven, Leuven, Belgium.|KU Leuven, University of Leuven, Leuven, Belgium.|KU Leuven, University of Leuven, Leuven, Belgium.|KU Leuven, University of Leuven, Leuven, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007181', '31498789', 'In various fields, statistical models of interest are analytically intractable and inference is usually performed using a simulation-based method. However elegant these methods are, they are often painstakingly slow and convergence is difficult to assess. As a result, statistical inference is greatly hampered by computational constraints. However, for a given statistical model, different users, even with different data, are likely to perform similar computations. Computations done by one user are potentially useful for other users with different data sets. We propose a pooling of resources across researchers to capitalize on this. More specifically, we preemptively chart out the entire space of possible model outcomes in a prepaid database. Using advanced interpolation techniques, any individual estimation problem can now be solved on the spot. The prepaid method can easily accommodate different priors as well as constraints on the parameters. We created prepaid databases for three challenging models and demonstrate how they can be distributed through an online parameter estimation service. Our method outperforms state-of-the-art estimation techniques in both speed (with a 23,000 to 100,000-fold speed up) and accuracy, and is able to handle previously quasi inestimable models.'),
(89920, 2019, 'plos', 'MHC binding affects the dynamics of different T-cell receptors in different ways', 'Knapp, Bernhard|van der Merwe, P Anton|Dushek, Omer|Deane, Charlotte M', 'Department of Basic Sciences, International University of Catalonia, Barcelona, Spain.|Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom.|Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom.|Department of Statistics, University of Oxford, Oxford, United Kingdom.', 'Spain|United Kingdom|United Kingdom|United Kingdom', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007338', '31498801', 'T cells use their T-cell receptors (TCRs) to scan other cells for antigenic peptides presented by MHC molecules (pMHC). If a TCR encounters a pMHC, it can trigger a signalling pathway that could lead to the activation of the T cell and the initiation of an immune response. It is currently not clear how the binding of pMHC to the TCR initiates signalling within the T cell. One hypothesis is that conformational changes in the TCR lead to further downstream signalling. Here we investigate four different TCRs in their free state as well as in their pMHC bound state using large scale molecular simulations totalling 26 000 ns. We find that the dynamical features within TCRs differ significantly between unbound TCR and TCR/pMHC simulations. However, apart from expected results such as reduced solvent accessibility and flexibility of the interface residues, these features are not conserved among different TCR types. The presence of a pMHC alone is not sufficient to cause cross-TCR-conserved dynamical features within a TCR. Our results argue against models of TCR triggering involving conserved allosteric conformational changes.'),
(89921, 2019, 'plos', 'From Escherichia coli mutant 13C labeling data to a core kinetic model: A kinetic model parameterization pipeline', 'Foster, Charles J|Gopalakrishnan, Saratram|Antoniewicz, Maciek R|Maranas, Costas D', 'Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Chemical and Biomolecular Engineering, University of Delaware. Newark, Delaware, United States of America.|Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'United States|United States|United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007319', '31504032', 'Kinetic models of metabolic networks offer the promise of quantitative phenotype prediction. The mechanistic characterization of enzyme catalyzed reactions allows for tracing the effect of perturbations in metabolite concentrations and reaction fluxes in response to genetic and environmental perturbation that are beyond the scope of stoichiometric models. In this study, we develop a two-step computational pipeline for the rapid parameterization of kinetic models of metabolic networks using a curated metabolic model and available 13C-labeling distributions under multiple genetic and environmental perturbations. The first step involves the elucidation of all intracellular fluxes in a core model of E. coli containing 74 reactions and 61 metabolites using 13C-Metabolic Flux Analysis (13C-MFA). Here, fluxes corresponding to the mid-exponential growth phase are elucidated for seven single gene deletion mutants from upper glycolysis, pentose phosphate pathway and the Entner-Doudoroff pathway. The computed flux ranges are then used to parameterize the same (i.e., k-ecoli74) core kinetic model for E. coli with 55 substrate-level regulations using the newly developed K-FIT parameterization algorithm. The K-FIT algorithm employs a combination of equation decomposition and iterative solution techniques to evaluate steady-state fluxes in response to genetic perturbations. k-ecoli74 predicted 86% of flux values for strains used during fitting within a single standard deviation of 13C-MFA estimated values. By performing both tasks using the same network, errors associated with lack of congruity between the two networks are avoided, allowing for seamless integration of data with model building. Product yield predictions and comparison with previously developed kinetic models indicate shifts in flux ranges and the presence or absence of mutant strains delivering flux towards pathways of interest from training data significantly impact predictive capabilities. Using this workflow, the impact of completeness of fluxomic datasets and the importance of specific genetic perturbations on uncertainties in kinetic parameter estimation are evaluated.'),
(89922, 2019, 'plos', 'Systematically understanding the immunity leading to CRPC progression', 'Ji, Zhiwei|Zhao, Weiling|Lin, Hui-Kuan|Zhou, Xiaobo', 'School of Biomedical Informatics, The University of Texas Health science center at Houston, Houston, Texas, United States of America.|School of Biomedical Informatics, The University of Texas Health science center at Houston, Houston, Texas, United States of America.|Department of Cancer Biology, Wake Forest Baptist Medical Center, Wake Forest University, Winston Salem, North Carolina, United States of America.|School of Biomedical Informatics, The University of Texas Health science center at Houston, Houston, Texas, United States of America.', 'United States|United States|United States|United States', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007344', '31504033', 'Prostate cancer (PCa) is the most commonly diagnosed malignancy and the second leading cause of cancer-related death in American men. Androgen deprivation therapy (ADT) has become a standard treatment strategy for advanced PCa. Although a majority of patients initially respond to ADT well, most of them will eventually develop castration-resistant PCa (CRPC). Previous studies suggest that ADT-induced changes in the immune microenvironment (mE) in PCa might be responsible for the failures of various therapies. However, the role of the immune system in CRPC development remains unclear. To systematically understand the immunity leading to CRPC progression and predict the optimal treatment strategy in silico, we developed a 3D Hybrid Multi-scale Model (HMSM), consisting of an ODE system and an agent-based model (ABM), to manipulate the tumor growth in a defined immune system. Based on our analysis, we revealed that the key factors (e.g. WNT5A, TRAIL, CSF1, etc.) mediated the activation of PC-Treg and PC-TAM interaction pathways, which induced the immunosuppression during CRPC progression. Our HMSM model also provided an optimal therapeutic strategy for improving the outcomes of PCa treatment.'),
(89923, 2019, 'plos', 'Role of dynamic nuclear deformation on genomic architecture reorganization', 'Seirin-Lee, Sungrim|Osakada, Fumitaka|Takeda, Junichi|Tashiro, Satoshi|Kobayashi, Ryo|Yamamoto, Takashi|Ochiai, Hiroshi', 'Department of Mathematics, School of Science, Hiroshima University, Higashi-Hiroshima, Japan.|PRESTO, Japan Science and Technology Agency, Kawaguchi, Japan.|Laboratory of Cellular Pharmacology, Graduate School of Pharmaceutical Sciences, Nagoya University, Nagoya, Japan.|Department of Cellular Biology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan.|Department of Mathematical and Life Sciences, Graduate School of Science, Hiroshima University, Higashi-Hiroshima, Japan.|Department of Mathematical and Life Sciences, Graduate School of Science, Hiroshima University, Higashi-Hiroshima, Japan.|PRESTO, Japan Science and Technology Agency, Kawaguchi, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007289', '31509522', 'Higher-order genomic architecture varies according to cell type and changes dramatically during differentiation. One of the remarkable examples of spatial genomic reorganization is the rod photoreceptor cell differentiation in nocturnal mammals. The inverted nuclear architecture found in adult mouse rod cells is formed through the reorganization of the conventional architecture during terminal differentiation. However, the mechanisms underlying these changes remain largely unknown. Here, we found that the dynamic deformation of nuclei via actomyosin-mediated contractility contributes to chromocenter clustering and promotes genomic architecture reorganization during differentiation by conducting an in cellulo experiment coupled with phase-field modeling. Similar patterns of dynamic deformation of the nucleus and a concomitant migration of the nuclear content were also observed in rod cells derived from the developing mouse retina. These results indicate that the common phenomenon of dynamic nuclear deformation, which accompanies dynamic cell behavior, can be a universal mechanism for spatiotemporal genomic reorganization.'),
(89924, 2019, 'plos', 'Predicting gene expression in the human malaria parasite Plasmodium falciparum using histone modification, nucleosome positioning, and 3D localization features', 'Read, David F|Cook, Kate|Lu, Yang Y|Le Roch, Karine G|Noble, William Stafford', 'Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.|Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.|Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.|Department of Molecular, Cell and Systems Biology, University of California, Riverside, California, United States of America.|Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States|United States|United States', 6, '-', 'Journal Article', '10.1371/journal.pcbi.1007329', '31509524', 'Empirical evidence suggests that the malaria parasite Plasmodium falciparum employs a broad range of mechanisms to regulate gene transcription throughout the organisms complex life cycle. To better understand this regulatory machinery, we assembled a rich collection of genomic and epigenomic data sets, including information about transcription factor (TF) binding motifs, patterns of covalent histone modifications, nucleosome occupancy, GC content, and global 3D genome architecture. We used these data to train machine learning models to discriminate between high-expression and low-expression genes, focusing on three distinct stages of the red blood cell phase of the Plasmodium life cycle. Our results highlight the importance of histone modifications and 3D chromatin architecture in Plasmodium transcriptional regulation and suggest that AP2 transcription factors may play a limited regulatory role, perhaps operating in conjunction with epigenetic factors.'),
(89925, 2019, 'plos', 'Generation of Binary Tree-Child phylogenetic networks', 'Cardona, Gabriel|Pons, Joan Carles|Scornavacca, Celine', 'Department of Mathematics and Computer Science, University of the Balearic Islands, Ctra. de Valldemossa Ctra. de Valldemossa km. 7.5. 07122 - Palma, Spain.|Department of Mathematics and Computer Science, University of the Balearic Islands, Ctra. de Valldemossa Ctra. de Valldemossa km. 7.5. 07122 - Palma, Spain.|Institut des Sciences de lEvolution (ISE-M), Université de Montpellier, CNRS, IRD, EPHE, 34095 Montpellier Cedex 5, France.', 'Spain|Spain|France', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007347', '31509525', 'Phylogenetic networks generalize phylogenetic trees by allowing the modelization of events of reticulate evolution. Among the different kinds of phylogenetic networks that have been proposed in the literature, the subclass of binary tree-child networks is one of the most studied ones. However, very little is known about the combinatorial structure of these networks. In this paper we address the problem of generating all possible binary tree-child (BTC) networks with a given number of leaves in an efficient way via reduction/augmentation operations that extend and generalize analogous operations for phylogenetic trees, and are biologically relevant. Since our solution is recursive, this also provides us with a recurrence relation giving an upper bound on the number of such networks. We also show how the operations introduced in this paper can be employed to extend the evolutive history of a set of sequences, represented by a BTC network, to include a new sequence. An implementation in python of the algorithms described in this paper, along with some computational experiments, can be downloaded from https://github.com/bielcardona/TCGenerators.'),
(89926, 2019, 'plos', 'Network trade-offs and homeostasis in Arabidopsis shoot architectures', 'Conn, Adam|Chandrasekhar, Arjun|Rongen, Martin van|Leyser, Ottoline|Chory, Joanne|Navlakha, Saket', 'Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, California, United States of America.|Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, California, United States of America.|Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom.|Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom.|Howard Hughes Medical Institute and Plant Biology Laboratory, Salk Institute for Biological Studies, La Jolla, California, United States of America.|Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, California, United States of America.', 'United States|United States|United Kingdom|United Kingdom|United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007325', '31509526', 'Understanding the optimization objectives that shape shoot architectures remains a critical problem in plant biology. Here, we performed 3D scanning of 152 Arabidopsis shoot architectures, including wildtype and 10 mutant strains, and we uncovered a design principle that describes how architectures make trade-offs between competing objectives. First, we used graph-theoretic analysis to show that Arabidopsis shoot architectures strike a Pareto optimal that can be captured as maximizing performance in transporting nutrients and minimizing costs in building the architecture. Second, we identify small sets of genes that can be mutated to shift the weight prioritizing one objective over the other. Third, we show that this prioritization weight feature is significantly less variable across replicates of the same genotype compared to other common plant traits (e.g., number of rosette leaves, total volume occupied). This suggests that this feature is a robust descriptor of a genotype, and that local variability in structure may be compensated for globally in a homeostatic manner. Overall, our work provides a framework to understand optimization trade-offs made by shoot architectures and provides evidence that these trade-offs can be modified genetically, which may aid plant breeding and selection efforts.'),
(89927, 2019, 'plos', 'Loop analysis of blood pressure/volume homeostasis', 'Burlando, Bruno|Blanchini, Franco|Giordano, Giulia', 'Department of Pharmacy (DIFAR), University of Genova, Genova, Italy.|Department of Mathematics, Computer Science and Physics, University of Udine, Udine, Italy.|Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands.', 'Italy|Italy|Netherlands', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007346', '31513566', 'We performed a mathematical analysis of the dynamic control loops regulating the vasomotor tone of vascular smooth muscle, blood volume, and mean arterial pressure, which involve the arginine vasopressin (AVP) system, the atrial natriuretic peptide system (ANP), and the renin-angiotensin-aldosterone system (RAAS). Our loop analysis of the AVP-ANP-RAAS system revealed the concurrent presence of two different regulatory mechanisms, which perform the same qualitative function: one affects blood pressure by regulating vasoconstriction, the other by regulating blood volume. Both the systems are candidate oscillators consisting of the negative-feedback loop of a monotone system: they admit a single equilibrium that can either be stable or give rise to oscillatory instability. Also a subsystem, which includes ANP and AVP stimulation of vascular smooth muscle cells, turns out to be a candidate oscillator composed of a monotone system with multiple negative feedback loops, and we show that its oscillatory potential is higher when the delays along all feedback loops are comparable. Our results give insight into the physiological mechanisms ruling long-term homeostasis of blood hydraulic parameters, which operate based on dynamical loops of interactions.'),
(89928, 2019, 'plos', 'Ten simple rules for helping newcomers become contributors to open projects', 'Sholler, Dan|Steinmacher, Igor|Ford, Denae|Averick, Mara|Hoye, Mike|Wilson, Greg', 'Berkeley Institute for Data Science, University of California Berkeley, Berkeley, California, United States of America.|School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, United States of America.|Department of Computer Science, North Carolina State University, Raleigh, North Carolina, United States of America.|RStudio, Inc., Boston, Massachusetts, United States of America.|Mozilla Corporation, Toronto, Ontario, Canada.|RStudio, Inc., Toronto, Ontario, Canada.', 'United States|United States|United States|United States|Canada|Canada', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007296', '31513567', '-'),
(89929, 2019, 'plos', 'Correction: Minimal model of interictal and ictal discharges Epileptor-2', 'Chizhov, Anton V|Zefirov, Artyom V|Amakhin, Dmitry V|Smirnova, Elena Yu|Zaitsev, Aleksey V', 'RStudio, Inc., Toronto, Ontario, Canada.|RStudio, Inc., Toronto, Ontario, Canada.|RStudio, Inc., Toronto, Ontario, Canada.|RStudio, Inc., Toronto, Ontario, Canada.|RStudio, Inc., Toronto, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1007359', '31513568', '[This corrects the article DOI: 10.1371/journal.pcbi.1006186.].'),
(89930, 2019, 'plos', 'Characterizing and dissociating multiple time-varying modulatory computations influencing neuronal activity', 'Niknam, Kaiser|Akbarian, Amir|Clark, Kelsey|Zamani, Yasin|Noudoost, Behrad|Nategh, Neda', 'Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, Utah, United States of America.|Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, Utah, United States of America.|Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, Utah, United States of America.|Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, Utah, United States of America.|Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, Utah, United States of America.|Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, Utah, United States of America.', 'United States|United States|United States|United States|United States|United States', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1007275', '31513570', 'In many brain areas, sensory responses are heavily modulated by factors including attentional state, context, reward history, motor preparation, learned associations, and other cognitive variables. Modelling the effect of these modulatory factors on sensory responses has proven challenging, mostly due to the time-varying and nonlinear nature of the underlying computations. Here we present a computational model capable of capturing and dissociating multiple time-varying modulatory effects on neuronal responses on the order of milliseconds. The models performance is tested on extrastriate perisaccadic visual responses in nonhuman primates. Visual neurons respond to stimuli presented around the time of saccades differently than during fixation. These perisaccadic changes include sensitivity to the stimuli presented at locations outside the neurons receptive field, which suggests a contribution of multiple sources to perisaccadic response generation. Current computational approaches cannot quantitatively characterize the contribution of each modulatory source in response generation, mainly due to the very short timescale on which the saccade takes place. In this study, we use a high spatiotemporal resolution experimental paradigm along with a novel extension of the generalized linear model framework (GLM), termed the sparse-variable GLM, to allow for time-varying model parameters representing the temporal evolution of the system with a resolution on the order of milliseconds. We used this model framework to precisely map the temporal evolution of the spatiotemporal receptive field of visual neurons in the middle temporal area during the execution of a saccade. Moreover, an extended model based on a factorization of the sparse-variable GLM allowed us to disassociate and quantify the contribution of individual sources to the perisaccadic response. Our results show that our novel framework can precisely capture the changes in sensitivity of neurons around the time of saccades, and provide a general framework to quantitatively track the role of multiple modulatory sources over time.'),
(89931, 2019, 'plos', 'Perspective: Dimensions of the scientific method', 'Voit, Eberhard O', 'Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States of America.', 'Georgia', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007279', '31513575', 'The scientific method has been guiding biological research for a long time. It not only prescribes the order and types of activities that give a scientific study validity and a stamp of approval but also has substantially shaped how we collectively think about the endeavor of investigating nature. The advent of high-throughput data generation, data mining, and advanced computational modeling has thrown the formerly undisputed, monolithic status of the scientific method into turmoil. On the one hand, the new approaches are clearly successful and expect the same acceptance as the traditional methods, but on the other hand, they replace much of the hypothesis-driven reasoning with inductive argumentation, which philosophers of science consider problematic. Intrigued by the enormous wealth of data and the power of machine learning, some scientists have even argued that significant correlations within datasets could make the entire quest for causation obsolete. Many of these issues have been passionately debated during the past two decades, often with scant agreement. It is proffered here that hypothesis-driven, data-mining-inspired, and allochthonous knowledge acquisition, based on mathematical and computational models, are vectors spanning a 3D space of an expanded scientific method. The combination of methods within this space will most certainly shape our thinking about nature, with implications for experimental design, peer review and funding, sharing of result, education, medical diagnostics, and even questions of litigation.'),
(89932, 2019, 'plos', 'Bioinformatics in Jordan: Status, challenges, and future directions', 'Bani Baker, Qanita|Nuser, Maryam S', 'Department of Computer Science, Jordan University of Science and Technology, Irbid, Jordan.|Department of Computer Science, Jordan University of Science and Technology, Irbid, Jordan.', 'Jordan|Jordan', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007202', '31513576', 'Bioinformatics plays a key role in supporting the life sciences. In this work, we examine bioinformatics in Jordan, beginning with the current status of bioinformatics education and research, then exploring the challenges of advancing bioinformatics, and finally looking to the future for how Jordanian bioinformatics research may develop.'),
(89933, 2019, 'plos', 'Long-term dynamics of measles in London: Titrating the impact of wars, the 1918 pandemic, and vaccination', 'Becker, Alexander D|Wesolowski, Amy|Bjørnstad, Ottar N|Grenfell, Bryan T', 'Department of Ecology and Evolutionary Biology, Princeton, New Jersey, United States of America.|Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.|Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Ecology and Evolutionary Biology, Princeton, New Jersey, United States of America.', 'Jersey|United States|United States|Jersey', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007305', '31513578', 'A key question in ecology is the relative impact of internal nonlinear dynamics and external perturbations on the long-term trajectories of natural systems. Measles has been analyzed extensively as a paradigm for consumer-resource dynamics due to the oscillatory nature of the host-pathogen life cycle, the abundance of rich data to test theory, and public health relevance. The dynamics of measles in London, in particular, has acted as a prototypical test bed for such analysis using incidence data from the pre-vaccination era (1944-1967). However, during this timeframe there were few external large-scale perturbations, limiting an assessment of the relative impact of internal and extra demographic perturbations to the host population. Here, we extended the previous London analyses to include nearly a century of data that also contains four major demographic changes: the First and Second World Wars, the 1918 influenza pandemic, and the start of a measles mass vaccination program. By combining mortality and incidence data using particle filtering methods, we show that a simple stochastic epidemic model, with minimal historical specifications, can capture the nearly 100 years of dynamics including changes caused by each of the major perturbations. We show that the majority of dynamic changes are explainable by the internal nonlinear dynamics of the system, tuned by demographic changes. In addition, the 1918 influenza pandemic and World War II acted as extra perturbations to this basic epidemic oscillator. Our analysis underlines that long-term ecological and epidemiological dynamics can follow very simple rules, even in a non-stationary population subject to significant perturbations and major secular changes.'),
(89934, 2019, 'plos', 'Weak coupling between intracellular feedback loops explains dissociation of clock gene dynamics', 'Schmal, Christoph|Ono, Daisuke|Myung, Jihwan|Pett, J Patrick|Honma, Sato|Honma, Ken-Ichi|Herzel, Hanspeter|Tokuda, Isao T', 'Department of Mechanical Engineering, Ritsumeikan University, Kusatsu, Japan.|Department of Neuroscience II, Research Institute of Environmental Medicine, Nagoya University, Nagoya, Japan.|Laboratory of Braintime, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan.|Institute for Theoretical Biology, Charité - Universitätsmedizin Berlin, Berlin, Germany.|Department of Chronomedicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan.|Department of Chronomedicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan.|Institute for Theoretical Biology, Charité - Universitätsmedizin Berlin, Berlin, Germany.|Department of Mechanical Engineering, Ritsumeikan University, Kusatsu, Japan.', 'Japan|Japan|-|Germany|Japan|Japan|Germany|Japan', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007330', '31513579', 'Circadian rhythms are generated by interlocked transcriptional-translational negative feedback loops (TTFLs), the molecular process implemented within a cell. The contributions, weighting and balancing between the multiple feedback loops remain debated. Dissociated, free-running dynamics in the expression of distinct clock genes has been described in recent experimental studies that applied various perturbations such as slice preparations, light pulses, jet-lag, and culture medium exchange. In this paper, we provide evidence that this presumably transient dissociation of circadian gene expression oscillations may occur at the single-cell level. Conceptual and detailed mechanistic mathematical modeling suggests that such dissociation is due to a weak interaction between multiple feedback loops present within a single cell. The dissociable loops provide insights into underlying mechanisms and general design principles of the molecular circadian clock.'),
(89935, 2019, 'plos', 'EMULSION: Transparent and flexible multiscale stochastic models in human, animal and plant epidemiology', 'Picault, Sébastien|Huang, Yu-Lin|Sicard, Vianney|Arnoux, Sandie|Beaunée, Gaël|Ezanno, Pauline', 'BIOEPAR, INRA, Oniris, Nantes, France.|BIOEPAR, INRA, Oniris, Nantes, France.|BIOEPAR, INRA, Oniris, Nantes, France.|BIOEPAR, INRA, Oniris, Nantes, France.|BIOEPAR, INRA, Oniris, Nantes, France.|BIOEPAR, INRA, Oniris, Nantes, France.', 'France|France|France|France|France|France', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007342', '31518349', 'Stochastic mechanistic epidemiological models largely contribute to better understand pathogen emergence and spread, and assess control strategies at various scales (from within-host to transnational scale). However, developing realistic models which involve multi-disciplinary knowledge integration faces three major challenges in predictive epidemiology: lack of readability once translated into simulation code, low reproducibility and reusability, and long development time compared to outbreak time scale. We introduce here EMULSION, an artificial intelligence-based software intended to address those issues and help modellers focus on model design rather than programming. EMULSION defines a domain-specific language to make all components of an epidemiological model (structure, processes, parameters…) explicit as a structured text file. This file is readable by scientists from other fields (epidemiologists, biologists, economists), who can contribute to validate or revise assumptions at any stage of model development. It is then automatically processed by EMULSION generic simulation engine, preventing any discrepancy between model description and implementation. The modelling language and simulation architecture both rely on the combination of advanced artificial intelligence methods (knowledge representation and multi-level agent-based simulation), allowing several modelling paradigms (from compartment- to individual-based models) at several scales (up to metapopulation). The flexibility of EMULSION and its capability to support iterative modelling are illustrated here through examples of progressive complexity, including late revisions of core model assumptions. EMULSION is also currently used to model the spread of several diseases in real pathosystems. EMULSION provides a command-line tool for checking models, producing model diagrams, running simulations, and plotting outputs. Written in Python 3, EMULSION runs on Linux, MacOS, and Windows. It is released under Apache-2.0 license. A comprehensive documentation with installation instructions, a tutorial and many examples are available from: https://sourcesup.renater.fr/www/emulsion-public.'),
(89936, 2019, 'plos', 'Deep attention networks reveal the rules of collective motion in zebrafish', 'Heras, Francisco J H|Romero-Ferrero, Francisco|Hinz, Robert C|de Polavieja, Gonzalo G', 'Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal.|Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal.|Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal.|Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal.', 'Portugal|Portugal|Portugal|Portugal', 5, '-', 'Journal Article', '10.1371/journal.pcbi.1007354', '31518357', 'A variety of simple models has been proposed to understand the collective motion of animals. These models can be insightful but may lack important elements necessary to predict the motion of each individual in the collective. Adding more detail increases predictability but can make models too complex to be insightful. Here we report that deep attention networks can obtain a model of collective behavior that is simultaneously predictive and insightful thanks to an organization in modules. When using simulated trajectories, the model recovers the ground-truth interaction rule used to generate them, as well as the number of interacting neighbours. For experimental trajectories of large groups of 60-100 zebrafish, Danio rerio, the model obtains that interactions between pairs can approximately be described as repulsive, attractive or as alignment, but only when moving slowly. At high velocities, interactions correspond only to alignment or alignment mixed with repulsion at close distances. The model also shows that each zebrafish decides where to move by aggregating information from the group as a weighted average over neighbours. Weights are higher for neighbours that are close, in a collision path or moving faster in frontal and lateral locations. The network also extracts that the number of interacting individuals is dynamical and typically in the range 8-22, with 1-10 more important ones. Our results suggest that each animal decides by dynamically selecting information from the collective.'),
(89937, 2019, 'plos', 'A flexible and generalizable model of online latent-state learning', 'Cochran, Amy L|Cisler, Josh M', 'Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, United States of America.|Department of Psychiatry, University of Wisconsin, Madison, Wisconsin, United States of America.', 'United States|United States', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007331', '31525176', 'Many models of classical conditioning fail to describe important phenomena, notably the rapid return of fear after extinction. To address this shortfall, evidence converged on the idea that learning agents rely on latent-state inferences, i.e. an ability to index disparate associations from cues to rewards (or penalties) and infer which index (i.e. latent state) is presently active. Our goal was to develop a model of latent-state inferences that uses latent states to predict rewards from cues efficiently and that can describe behavior in a diverse set of experiments. The resulting model combines a Rescorla-Wagner rule, for which updates to associations are proportional to prediction error, with an approximate Bayesian rule, for which beliefs in latent states are proportional to prior beliefs and an approximate likelihood based on current associations. In simulation, we demonstrate the models ability to reproduce learning effects both famously explained and not explained by the Rescorla-Wagner model, including rapid return of fear after extinction, the Hall-Pearce effect, partial reinforcement extinction effect, backwards blocking, and memory modification. Lastly, we derive our model as an online algorithm to maximum likelihood estimation, demonstrating it is an efficient approach to outcome prediction. Establishing such a framework is a key step towards quantifying normative and pathological ranges of latent-state inferences in various contexts.'),
(89938, 2019, 'plos', 'Close spatial arrangement of mutants favors and disfavors fixation', 'Xiao, Yunming|Wu, Bin', 'School of Sciences, Beijing University of Posts and Telecommunications, Beijing, China.|School of Sciences, Beijing University of Posts and Telecommunications, Beijing, China.', 'China|China', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007212', '31525178', 'Cooperation is ubiquitous across all levels of biological systems ranging from microbial communities to human societies. It, however, seemingly contradicts the evolutionary theory, since cooperators are exploited by free-riders and thus are disfavored by natural selection. Many studies based on evolutionary game theory have tried to solve the puzzle and figure out the reason why cooperation exists and how it emerges. Network reciprocity is one of the mechanisms to promote cooperation, where nodes refer to individuals and links refer to social relationships. The spatial arrangement of mutant individuals, which refers to the clustering of mutants, plays a key role in network reciprocity. Besides, many other mechanisms supporting cooperation suggest that the clustering of mutants plays an important role in the expansion of mutants. However, the clustering of mutants and the game dynamics are typically coupled. It is still unclear how the clustering of mutants alone alters the evolutionary dynamics. To this end, we employ a minimal model with frequency independent fitness on a circle. It disentangles the clustering of mutants from game dynamics. The distance between two mutants on the circle is adopted as a natural indicator for the clustering of mutants or assortment. We find that the assortment is an amplifier of the selection for the connected mutants compared with the separated ones. Nevertheless, as mutants are separated, the more dispersed mutants are, the greater the chance of invasion is. It gives rise to the non-monotonic effect of clustering, which is counterintuitive. On the other hand, we find that less assortative mutants speed up fixation. Our model shows that the clustering of mutants plays a non-trivial role in fixation, which has emerged even if the game interaction is absent.'),
(89939, 2019, 'plos', 'Deep learning as a tool for neural data analysis: Speech classification and cross-frequency coupling in human sensorimotor cortex', 'Livezey, Jesse A|Bouchard, Kristofer E|Chang, Edward F', 'Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Department of Neurological Surgery and Department of Physiology, University of California, San Francisco, San Francisco, California, United States of America.', 'United States|United States|United States', 3, '-', 'Journal Article', '10.1371/journal.pcbi.1007091', '31525179', 'A fundamental challenge in neuroscience is to understand what structure in the world is represented in spatially distributed patterns of neural activity from multiple single-trial measurements. This is often accomplished by learning a simple, linear transformations between neural features and features of the sensory stimuli or motor task. While successful in some early sensory processing areas, linear mappings are unlikely to be ideal tools for elucidating nonlinear, hierarchical representations of higher-order brain areas during complex tasks, such as the production of speech by humans. Here, we apply deep networks to predict produced speech syllables from a dataset of high gamma cortical surface electric potentials recorded from human sensorimotor cortex. We find that deep networks had higher decoding prediction accuracy compared to baseline models. Having established that deep networks extract more task relevant information from neural data sets relative to linear models (i.e., higher predictive accuracy), we next sought to demonstrate their utility as a data analysis tool for neuroscience. We first show that deep networks confusions revealed hierarchical latent structure in the neural data, which recapitulated the underlying articulatory nature of speech motor control. We next broadened the frequency features beyond high-gamma and identified a novel high-gamma-to-beta coupling during speech production. Finally, we used deep networks to compare task-relevant information in different neural frequency bands, and found that the high-gamma band contains the vast majority of information relevant for the speech prediction task, with little-to-no additional contribution from lower-frequency amplitudes. Together, these results demonstrate the utility of deep networks as a data analysis tool for basic and applied neuroscience.'),
(89940, 2019, 'plos', 'Frequency spectrum of chemical fluctuation: A probe of reaction mechanism and dynamics', 'Song, Sanggeun|Yang, Gil-Suk|Park, Seong Jun|Hong, Sungguan|Kim, Ji-Hyun|Sung, Jaeyoung', 'Center for Chemical Dynamics in Living Cells, Chung-Ang University, Seoul, Korea.|Center for Chemical Dynamics in Living Cells, Chung-Ang University, Seoul, Korea.|Center for Chemical Dynamics in Living Cells, Chung-Ang University, Seoul, Korea.|Department of Chemistry, Chung-Ang University, Seoul, Korea.|Center for Chemical Dynamics in Living Cells, Chung-Ang University, Seoul, Korea.|Center for Chemical Dynamics in Living Cells, Chung-Ang University, Seoul, Korea.', '-|-|-|-|-|-', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007356', '31525182', 'Even in the steady-state, the number of biomolecules in living cells fluctuates dynamically, and the frequency spectrum of this chemical fluctuation carries valuable information about the dynamics of the reactions creating these biomolecules. Recent advances in single-cell techniques enable direct monitoring of the time-traces of the protein number in each cell, however, it is not yet clear how the stochastic dynamics of these time-traces is related to the reaction mechanism and dynamics. Here, we derive a rigorous relation between the frequency-spectrum of the product number fluctuation and the reaction mechanism and dynamics, starting from a generalized master equation. This relation enables us to analyze the time-traces of the protein number and extract information about dynamics of mRNA number and transcriptional regulation, which cannot be directly observed by current experimental techniques. We demonstrate our frequency spectrum analysis of protein number fluctuation, using the gene network model of luciferase expression under the control of the Bmal 1a promoter in mouse fibroblast cells. We also discuss how the dynamic heterogeneity of transcription and translation rates affects the frequency-spectra of the mRNA and protein number.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89941, 2019, 'plos', 'Fast and near-optimal monitoring for healthcare acquired infection outbreaks', 'Adhikari, Bijaya|Lewis, Bryan|Vullikanti, Anil|Jiménez, José Mauricio|Prakash, B Aditya', 'Department of Computer Science, Virginia Tech, Blacksburg, Virginia, United States of America.|Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, Virginia, United States of America.|Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Systems Engineering, United States Military Academy, West Point, New York, United States of America.|Department of Computer Science, Virginia Tech, Blacksburg, Virginia, United States of America.', 'United States|United States|United States|United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007284', '31525183', 'According to the Centers for Disease Control and Prevention (CDC), one in twenty five hospital patients are infected with at least one healthcare acquired infection (HAI) on any given day. Early detection of possible HAI outbreaks help practitioners implement countermeasures before the infection spreads extensively. Here, we develop an efficient data and model driven method to detect outbreaks with high accuracy. We leverage mechanistic modeling of C. difficile infection, a major HAI disease, to simulate its spread in a hospital wing and design efficient near-optimal algorithms to select people and locations to monitor using an optimization formulation. Results show that our strategy detects up to 95% of future C. difficile outbreaks. We design our method by incorporating specific hospital practices (like swabbing for infections) as well. As a result, our method outperforms state-of-the-art algorithms for outbreak detection. Finally, a qualitative study of our result shows that the people and locations we select to monitor as sensors are intuitive and meaningful.'),
(89942, 2019, 'plos', 'Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints', 'Venkatramanan, Srinivasan|Chen, Jiangzhuo|Fadikar, Arindam|Gupta, Sandeep|Higdon, Dave|Lewis, Bryan|Marathe, Madhav|Mortveit, Henning|Vullikanti, Anil', 'Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, Virginia, United States of America.|Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Statistics, Virginia Tech, Blacksburg, Virginia, United States of America.|Biocomplexity Institute, Virginia Tech, Blacksburg, Virginia, United States of America.|Department of Statistics, Virginia Tech, Blacksburg, Virginia, United States of America.|Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, Virginia, United States of America.|Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, Virginia, United States of America.|Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, Virginia, United States of America.|Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, Virginia, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007111', '31525184', 'Prophylactic interventions such as vaccine allocation are some of the most effective public health policy planning tools. The supply of vaccines, however, is limited and an important challenge is to optimally allocate the vaccines to minimize epidemic impact. This resource allocation question (which we refer to as VaccIntDesign) has multiple dimensions: when, where, to whom, etc. Most of the existing literature in this topic deals with the latter (to whom), proposing policies that prioritize individuals by age and disease risk. However, since seasonal influenza spread has a typical spatial trend, and due to the temporal constraints enforced by the availability schedule, the when and where problems become equally, if not more, relevant. In this paper, we study the VaccIntDesign problem in the context of seasonal influenza spread in the United States. We develop a national scale metapopulation model for influenza that integrates both short and long distance human mobility, along with realistic data on vaccine uptake. We also design GreedyAlloc, a greedy algorithm for allocating the vaccine supply at the state level under temporal constraints and show that such a strategy improves over the current baseline of pro-rata allocation, and the improvement is more pronounced for higher vaccine efficacy and moderate flu season intensity. Further, the resulting strategy resembles a ring vaccination applied spatiallyacross the US.'),
(89943, 2019, 'plos', 'Complex genetic and epigenetic regulation deviates gene expression from a unifying global transcriptional program', 'Chagoyen, Mónica|Poyatos, Juan F', 'Computational Systems Biology Group (CNB-CSIC), Madrid, Spain.|Logic of Genomic Systems Laboratory (CNB-CSIC), Madrid, Spain.', 'Spain|Spain', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007353', '31527866', 'Environmental or genetic perturbations lead to gene expression changes. While most analyses of these changes emphasize the presence of qualitative differences on just a few genes, we now know that changes are widespread. This large-scale variation has been linked to the exclusive influence of a global transcriptional program determined by the new physiological state of the cell. However, given the sophistication of eukaryotic regulation, we expect to have a complex architecture of specific control affecting this program. Here, we examine this architecture. Using data of Saccharomyces cerevisiae expression in different nutrient conditions, we first propose a five-sector genome partition, which integrates earlier models of resource allocation, as a framework to examine the deviations from the global control. In this scheme, we recognize invariant genes, whose regulation is dominated by physiology, specific genes, which substantially depart from it, and two additional classes that contain the frequently assumed growth-dependent genes. Whereas the invariant class shows a considerable absence of specific regulation, the rest is enriched by regulation at the level of transcription factors (TFs) and epigenetic modulators. We nevertheless find markedly different strategies in how these classes deviate. On the one hand, there are TFs that act in a unique way between partition constituents, and on the other, the action of chromatin modifiers is significantly diverse. The balance between regulatory strategies ultimately modulates the action of the general transcription machinery and therefore limits the possibility of establishing a unifying program of expression change at a genomic scale.'),
(89944, 2019, 'plos', 'Predicting gene regulatory interactions based on spatial gene expression data and deep learning', 'Yang, Yang|Fang, Qingwei|Shen, Hong-Bin', 'Center for Brain-Like Computing and Machine Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.|School of Bio-medical Engineering, Shanghai Jiao Tong University, Shanghai, China.|Institute of Image Processing and Pattern Recognition, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai Jiao Tong University, Shanghai, China.', 'China|China|China', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007324', '31527870', 'Reverse engineering of gene regulatory networks (GRNs) is a central task in systems biology. Most of the existing methods for GRN inference rely on gene co-expression analysis or TF-target binding information, where the determination of co-expression is often unreliable merely based on gene expression levels, and the TF-target binding data from high-throughput experiments may be noisy, leading to a high ratio of false links and missed links, especially for large-scale networks. In recent years, the microscopy images recording spatial gene expression have become a new resource in GRN reconstruction, as the spatial and temporal expression patterns contain much abundant gene interaction information. Till now, the spatial expression resources have been largely underexploited, and only a few traditional image processing methods have been employed in the image-based GRN reconstruction. Moreover, co-expression analysis using conventional measurements based on image similarity may be inaccurate, because it is the local-pattern consistency rather than global-image-similarity that determines gene-gene interactions. Here we present GripDL (Gene regulatory interaction prediction via Deep Learning), which incorporates high-confidence TF-gene regulation knowledge from previous studies, and constructs GRNs for Drosophila eye development based on Drosophila embryonic gene expression images. Benefitting from the powerful representation ability of deep neural networks and the supervision information of known interactions, the new method outperforms traditional methods with a large margin and reveals new intriguing knowledge about Drosophila eye development.'),
(89945, 2019, 'plos', 'Unified feature association networks through integration of transcriptomic and proteomic data', 'McClure, Ryan S|Wendler, Jason P|Adkins, Joshua N|Swanstrom, Jesica|Baric, Ralph|Kaiser, Brooke L Deatherage|Oxford, Kristie L|Waters, Katrina M|McDermott, Jason E', 'Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA, United States of America.|Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA, United States of America.|Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA, United States of America.|Department of Microbiology and Immunology, School of Medicine, University of North Carolina, Chapel Hill, Chapel Hill, NC, United States of America.|Department of Microbiology and Immunology, School of Medicine, University of North Carolina, Chapel Hill, Chapel Hill, NC, United States of America.|Signatures Science and Technology Division, Pacific Northwest National Laboratory, Richland WA, United States of America.|Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA, United States of America.|Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA, United States of America.|Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007241', '31527878', 'High-throughput multi-omics studies and corresponding network analyses of multi-omic data have rapidly expanded their impact over the last 10 years. As biological features of different types (e.g. transcripts, proteins, metabolites) interact within cellular systems, the greatest amount of knowledge can be gained from networks that incorporate multiple types of -omic data. However, biological and technical sources of variation diminish the ability to detect cross-type associations, yielding networks dominated by communities comprised of nodes of the same type. We describe here network building methods that can maximize edges between nodes of different data types leading to integrated networks, networks that have a large number of edges that link nodes of different-omic types (transcripts, proteins, lipids etc). We systematically rank several network inference methods and demonstrate that, in many cases, using a random forest method, GENIE3, produces the most integrated networks. This increase in integration does not come at the cost of accuracy as GENIE3 produces networks of approximately the same quality as the other network inference methods tested here. Using GENIE3, we also infer networks representing antibody-mediated Dengue virus cell invasion and receptor-mediated Dengue virus invasion. A number of functional pathways showed centrality differences between the two networks including genes responding to both GM-CSF and IL-4, which had a higher centrality value in an antibody-mediated vs. receptor-mediated Dengue network. Because a biological system involves the interplay of many different types of molecules, incorporating multiple data types into networks will improve their use as models of biological systems. The methods explored here are some of the first to specifically highlight and address the challenges associated with how such multi-omic networks can be assembled and how the greatest number of interactions can be inferred from different data types. The resulting networks can lead to the discovery of new host response patterns and interactions during viral infection, generate new hypotheses of pathogenic mechanisms and confirm mechanisms of disease.'),
(89946, 2019, 'plos', '3D spatial organization and network-guided comparison of mutation profiles in Glioblastoma reveals similarities across patients', 'Dincer, Cansu|Kaya, Tugba|Keskin, Ozlem|Gursoy, Attila|Tuncbag, Nurcan', 'Department of Health Informatics, Graduate School of Informatics, METU, Ankara, Turkey.|Department of Health Informatics, Graduate School of Informatics, METU, Ankara, Turkey.|Department of Chemical and Biological Engineering, Koc University, Istanbul, Turkey.|Research Center for Translational Medicine (KUTTAM), Koc University, Istanbul, Turkey.|Department of Health Informatics, Graduate School of Informatics, METU, Ankara, Turkey.', 'Turkey|Turkey|Turkey|Turkey|Turkey', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1006789', '31527881', 'Glioblastoma multiforme (GBM) is the most aggressive type of brain tumor. Molecular heterogeneity is a hallmark of GBM tumors that is a barrier in developing treatment strategies. In this study, we used the nonsynonymous mutations of GBM tumors deposited in The Cancer Genome Atlas (TCGA) and applied a systems level approach based on biophysical characteristics of mutations and their organization in patient-specific subnetworks to reduce inter-patient heterogeneity and to gain potential clinically relevant insights. Approximately 10% of the mutations are located in patches which are defined as the set of residues spatially in close proximity that are mutated across multiple patients. Grouping mutations as 3D patches reduces the heterogeneity across patients. There are multiple patches that are relatively small in oncogenes, whereas there are a small number of very large patches in tumor suppressors. Additionally, different patches in the same protein are often located at different domains that can mediate different functions. We stratified the patients into five groups based on their potentially affected pathways that are revealed from the patient-specific subnetworks. These subnetworks were constructed by integrating mutation profiles of the patients with the interactome data. Network-guided clustering showed significant association between the groups and patient survival (P-value = 0.0408). Also, each group carries a set of signature 3D mutation patches that affect predominant pathways. We integrated drug sensitivity data of GBM cell lines with the mutation patches and the patient groups to analyze the possible therapeutic outcome of these patches. We found that Pazopanib might be effective in Group 3 by targeting CSF1R. Additionally, inhibiting ATM that is a mediator of PTEN phosphorylation may be ineffective in Group 2. We believe that from mutations to networks and eventually to clinical and therapeutic data, this study provides a novel perspective in the network-guided precision medicine.'),
(89947, 2019, 'plos', 'Multi-cell ECM compaction is predictable via superposition of nonlinear cell dynamics linearized in augmented state space', 'Mayalu, Michaëlle N|Kim, Min-Cheol|Asada, H Harry', 'Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006798', '31539369', 'Cells interacting through an extracellular matrix (ECM) exhibit emergent behaviors resulting from collective intercellular interaction. In wound healing and tissue development, characteristic compaction of ECM gel is induced by multiple cells that generate tensions in the ECM fibers and coordinate their actions with other cells. Computational prediction of collective cell-ECM interaction based on first principles is highly complex especially as the number of cells increase. Here, we introduce a computationally-efficient method for predicting nonlinear behaviors of multiple cells interacting mechanically through a 3-D ECM fiber network. The key enabling technique is superposition of single cell computational models to predict multicellular behaviors. While cell-ECM interactions are highly nonlinear, they can be linearized accurately with a unique method, termed Dual-Faceted Linearization. This method recasts the original nonlinear dynamics in an augmented space where the system behaves more linearly. The independent state variables are augmented by combining auxiliary variables that inform nonlinear elements involved in the system. This computational method involves a) expressing the original nonlinear state equations with two sets of linear dynamic equations b) reducing the order of the augmented linear system via principal component analysis and c) superposing individual single cell-ECM dynamics to predict collective behaviors of multiple cells. The method is computationally efficient compared to original nonlinear dynamic simulation and accurate compared to traditional Taylor expansion linearization. Furthermore, we reproduce reported experimental results of multi-cell induced ECM compaction.'),
(89948, 2019, 'plos', 'Why do G-quadruplexes dimerize through the 5-ends? Driving forces for G4 DNA dimerization examined in atomic detail', 'Kogut, Mateusz|Kleist, Cyprian|Czub, Jacek', 'Department of Physical Chemistry, Gdansk University of Technology, Gdansk, Poland.|Department of Physical Chemistry, Gdansk University of Technology, Gdansk, Poland.|Department of Physical Chemistry, Gdansk University of Technology, Gdansk, Poland.', 'Poland|Poland|Poland', 6, '-', 'Journal Article', '10.1371/journal.pcbi.1007383', '31539370', 'G-quadruplexes (G4) are secondary structures formed by guanine-rich nucleic acid sequences and shown to exist in living cells where they participate in regulation of gene expression and chromosome maintenance. G-quadruplexes with solvent-exposed guanine tetrads show the tendency to associate together through cofacial stacking, which may be important for packaging of G4-forming sequences and allows for the design of higher-order G4 DNA structures. To understand the molecular driving forces for G4 association, here, we study the binding interaction between two parallel-stranded G-quadruplexes using all-atom molecular dynamics simulations. The predicted dimerization free energies show that direct binding through the 5-G-tetrads is the most preferred of all possible end-to-end stacking orientations, consistently with all available experimental data. Decomposition of dimerization enthalpies in combination with simulations at varying ionic strength further indicate that the observed orientational preferences arise from a fine balance between the electrostatic repulsion of the sugar-phosphate backbones and favorable counterion binding at the dimeric interface. We also demonstrate how these molecular-scale findings can be used to devise means of controlling G4 dimerization equilibrium, e.g., by altering salt concentration and using G4-targeted ligands.'),
(89949, 2019, 'plos', 'Correction: Comprehensively benchmarking applications for detecting copy number variation', 'Zhang, Le|Bai, Wanyu|Yuan, Na|Du, Zhenglin', 'Department of Physical Chemistry, Gdansk University of Technology, Gdansk, Poland.|Department of Physical Chemistry, Gdansk University of Technology, Gdansk, Poland.|Department of Physical Chemistry, Gdansk University of Technology, Gdansk, Poland.|Department of Physical Chemistry, Gdansk University of Technology, Gdansk, Poland.', 'Poland|Poland|Poland|Poland', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1007367', '31539372', '[This corrects the article DOI: 10.1371/journal.pcbi.1007069.].'),
(89950, 2019, 'plos', 'A scale-free analysis of the HIV-1 genome demonstrates multiple conserved regions of structural and functional importance', 'Skittrall, Jordan P|Ingemarsdotter, Carin K|Gog, Julia R|Lever, Andrew M L', 'Department of Medicine, University of Cambridge, Addenbrookes Hospital, Cambridge, United Kingdom.|Department of Medicine, University of Cambridge, Addenbrookes Hospital, Cambridge, United Kingdom.|Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Centre for Mathematical Sciences, Cambridge, United Kingdom.|Department of Medicine, University of Cambridge, Addenbrookes Hospital, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007345', '31545786', 'HIV-1 replicates via a low-fidelity polymerase with a high mutation rate, strong conservation of individual nucleotides is highly indicative of the presence of critical structural or functional properties. Identifying such conservation can reveal novel insights into viral behaviour. We analysed 3651 publicly available sequences for the presence of nucleic acid conservation beyond that required by amino acid constraints, using a novel scale-free method that identifies regions of outlying score together with a codon scoring algorithm. Sequences with outlying score were further analysed using an algorithm for producing local RNA folds whilst accounting for alignment properties. 11 different conserved regions were identified, some corresponding to well-known cis-acting functions of the HIV-1 genome but also others whose conservation has not previously been noted. We identify rational causes for many of these, including cis functions, possible additional reading frame usage, a plausible mechanism by which the central polypurine tract primes second-strand DNA synthesis and a conformational stabilising function of a region at the 5 end of env.'),
(89951, 2019, 'plos', 'Dimensions of control for subthreshold oscillations and spontaneous firing in dopamine neurons', 'Rumbell, Timothy|Kozloski, James', 'IBM Research, Computational Biology Center, Thomas J. Watson Research Laboratories, Yorktown Heights, New York, United States of America.|IBM Research, Computational Biology Center, Thomas J. Watson Research Laboratories, Yorktown Heights, New York, United States of America.', 'United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007375', '31545787', 'Dopaminergic neurons (DAs) of the rodent substantia nigra pars compacta (SNc) display varied electrophysiological properties in vitro. Despite this, projection patterns and functional inputs from DAs to other structures are conserved, so in vivo delivery of consistent, well-timed dopamine modulation to downstream circuits must be coordinated. Here we show robust coordination by linear parameter controllers, discovered through powerful mathematical analyses of data and models, and from which consistent control of DA subthreshold oscillations (STOs) and spontaneous firing emerges. These units of control represent coordinated intracellular variables, sufficient to regulate complex cellular properties with radical simplicity. Using an evolutionary algorithm and dimensionality reduction, we discovered metaparameters, which when regressed against STO features, revealed a 2-dimensional control plane for the neurons 22-dimensional parameter space that fully maps the natural range of DA subthreshold electrophysiology. This plane provided a basis for spiking currents to reproduce a large range of the naturally occurring spontaneous firing characteristics of SNc DAs. From it we easily produced a unique population of models, derived using unbiased parameter search, that show good generalization to channel blockade and compensatory intracellular mechanisms. From this population of models, we then discovered low-dimensional controllers for regulating spontaneous firing properties, and gain insight into how currents active in different voltage regimes interact to produce the emergent activity of SNc DAs. Our methods therefore reveal simple regulators of neuronal function lurking in the complexity of combined ion channel dynamics.'),
(89952, 2019, 'plos', 'Time scales and wave formation in non-linear spatial public goods games', 'Kimmel, Gregory J|Gerlee, Philip|Altrock, Philipp M', 'Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America.|Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden.|Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America.', 'United States|Sweden|United States', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007361', '31545788', 'The co-evolutionary dynamics of competing populations can be strongly affected by frequency-dependent selection and spatial population structure. As co-evolving populations grow into a spatial domain, their initial spatial arrangement and their growth rate differences are important factors that determine the long-term outcome. We here model producer and free-rider co-evolution in the context of a diffusive public good (PG) that is produced by the producers at a cost but evokes local concentration-dependent growth benefits to all. The benefit of the PG can be non-linearly dependent on public good concentration. We consider the spatial growth dynamics of producers and free-riders in one, two and three dimensions by modeling producer cell, free-rider cell and public good densities in space, driven by the processes of birth, death and diffusion (cell movement and public good distribution). Typically, one population goes extinct, but the time-scale of this process varies with initial conditions and the growth rate functions. We establish that spatial variation is transient regardless of dimensionality, and that structured initial conditions lead to increasing times to get close to an extinction state, called xcexb5-extinction time. Further, we find that uncorrelated initial spatial structures do not influence this xcexb5-extinction time in comparison to a corresponding well-mixed (non-spatial) system. In order to estimate the xcexb5-extinction time of either free-riders or producers we derive a slow manifold solution. For invading populations, i.e. for populations that are initially highly segregated, we observe a traveling wave, whose speed can be calculated. Our results provide quantitative predictions for the transient spatial dynamics of cooperative traits under pressure of extinction.'),
(89953, 2019, 'plos', 'Quantifying model evidence for yellow fever transmission routes in Africa', 'Gaythorpe, Katy A M|Jean, Kévin|Cibrelus, Laurence|Garske, Tini', 'School of Public Health, Imperial College London, London, United Kingdom.|Laboratoire MESuRS, Conservatoire National des Arts et Métiers, Paris, France.|Infectious Hazard Management Department, World Health Organisation, Geneva, Switzerland.|School of Public Health, Imperial College London, London, United Kingdom.', 'United Kingdom|France|Switzerland|United Kingdom', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007355', '31545790', 'Yellow fever is a vector-borne disease endemic in tropical regions of Africa, where 90% of the global burden occurs, and Latin America. It is notoriously under-reported with uncertainty arising from a complex transmission cycle including a sylvatic reservoir and non-specific symptom set. Resulting estimates of burden, particularly in Africa, are highly uncertain. We examine two established models of yellow fever transmission within a Bayesian model averaging framework in order to assess the relative evidence for each models assumptions and to highlight possible data gaps. Our models assume contrasting scenarios of the yellow fever transmission cycle in Africa. The first takes the force of infection in each province to be static across the observation period, this is synonymous with a constant infection pressure from the sylvatic reservoir. The second model assumes the majority of transmission results from the urban cycle, in this case, the force of infection is dynamic and defined through a fixed value of R0 in each province. Both models are coupled to a generalised linear model of yellow fever occurrence which uses environmental covariates to allow us to estimate transmission intensity in areas where data is sparse. We compare these contrasting descriptions of transmission through a Bayesian framework and trans-dimensional Markov chain Monte Carlo sampling in order to assess each models evidence given the range of uncertainty in parameter values. The resulting estimates allow us to produce Bayesian model averaged predictions of yellow fever burden across the African endemic region. We find strong support for the static force of infection model which suggests a higher proportion of yellow fever transmission occurs as a result of infection from an external source such as the sylvatic reservoir. However, the model comparison highlights key data gaps in serological surveys across the African endemic region. As such, conclusions concerning the most prevalent transmission routes for yellow fever will be limited by the sparsity of data which is particularly evident in the areas with highest predicted transmission intensity. Our model and estimation approach provides a robust framework for model comparison and predicting yellow fever burden in Africa. However, key data gaps increase uncertainty surrounding estimates of model parameters and evidence. As more mathematical models are developed to address new research questions, it is increasingly important to compare them with established modelling approaches to highlight uncertainty in structures and data.'),
(89954, 2019, 'plos', 'Heterogeneous responses to low level death receptor activation are explained by random molecular assembly of the Caspase-8 activation platform', 'Matveeva, Anna|Fichtner, Michael|McAllister, Katherine|McCann, Christopher|Sturrock, Marc|Longley, Daniel B|Prehn, Jochen H M', 'Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland.|Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland.|Centre for Cancer Research and Cell Biology, Queens University, Belfast, United Kingdom.|Centre for Cancer Research and Cell Biology, Queens University, Belfast, United Kingdom.|Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland.|Centre for Cancer Research and Cell Biology, Queens University, Belfast, United Kingdom.|Centre for Systems Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland.', 'Ireland|Ireland|United Kingdom|United Kingdom|Ireland|United Kingdom|Ireland', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007374', '31553717', 'Ligand binding to death receptors activates apoptosis in cancer cells. Stimulation of death receptors results in the formation of intracellular multiprotein platforms that either activate the apoptotic initiator Caspase-8 to trigger cell death, or signal through kinases to initiate inflammatory and cell survival signalling. Two of these platforms, the Death-Inducing Signalling Complex (DISC) and the RIPoptosome, also initiate necroptosis by building filamentous scaffolds that lead to the activation of mixed lineage kinase domain-like pseudokinase. To explain cell decision making downstream of death receptor activation, we developed a semi-stochastic model of DISC/RIPoptosome formation. The model is a hybrid of a direct Gillespie stochastic simulation algorithm for slow assembly of the RIPoptosome and a deterministic model of downstream caspase activation. The model explains how alterations in the level of death receptor-ligand complexes, their clustering properties and intrinsic molecular fluctuations in RIPoptosome assembly drive heterogeneous dynamics of Caspase-8 activation. The model highlights how kinetic proofreading leads to heterogeneous cell responses and results in fractional cell killing at low levels of receptor stimulation. It reveals that the noise in Caspase-8 activation-exclusively caused by the stochastic molecular assembly of the DISC/RIPoptosome platform-has a key function in extrinsic apoptotic stimuli recognition.'),
(89955, 2019, 'plos', 'Invariant neural responses for sensory categories revealed by the time-varying information for communication calls', 'Elie, Julie E|Theunissen, Frédéric E', 'Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California, United States of America.|Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California, United States of America.', 'United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006698', '31557151', 'Although information theoretic approaches have been used extensively in the analysis of the neural code, they have yet to be used to describe how information is accumulated in time while sensory systems are categorizing dynamic sensory stimuli such as speech sounds or visual objects. Here, we present a novel method to estimate the cumulative information for stimuli or categories. We further define a time-varying categorical information index that, by comparing the information obtained for stimuli versus categories of these same stimuli, quantifies invariant neural representations. We use these methods to investigate the dynamic properties of avian cortical auditory neurons recorded in zebra finches that were listening to a large set of call stimuli sampled from the complete vocal repertoire of this species. We found that the time-varying rates carry 5 times more information than the mean firing rates even in the first 100 ms. We also found that cumulative information has slow time constants (100-600 ms) relative to the typical integration time of single neurons, reflecting the fact that the behaviorally informative features of auditory objects are time-varying sound patterns. When we correlated firing rates and information values, we found that average information correlates with average firing rate but that higher-rates found at the onset response yielded similar information values as the lower-rates found in the sustained response: the onset and sustained response of avian cortical auditory neurons provide similar levels of independent information about call identity and call-type. Finally, our information measures allowed us to rigorously define categorical neurons, these categorical neurons show a high degree of invariance for vocalizations within a call-type. Peak invariance is found around 150 ms after stimulus onset. Surprisingly, call-type invariant neurons were found in both primary and secondary avian auditory areas.'),
(89956, 2019, 'plos', 'Ten simple rules to create biological network figures for communication', 'Marai, G Elisabeta|Pinaud, Bruno|Bühler, Katja|Lex, Alexander|Morris, John H', 'Electronic Visualization Laboratory, University of Illinois at Chicago, Chicago, Illinois, United States of America.|Laboratoire Bordelais de Recherche en Informatique, University of Bordeaux, Bordeaux, France.|Biomedical Image Informatics Department, VRVis Research Center, Vienna, Austria.|Department of Computer Science, University of Utah, Salt Lake City, Utah, United States of America.|Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, United States of America.', 'United States|France|Austria|United States|United States', 3, '-', 'Editorial', '10.1371/journal.pcbi.1007244', '31557157', 'Biological network figures are ubiquitous in the biology and medical literature. On the one hand, a good network figure can quickly provide information about the nature and degree of interactions between items and enable inferences about the reason for those interactions. On the other hand, good network figures are difficult to create. In this paper, we outline 10 simple rules for creating biological network figures for communication, from choosing layouts, to applying color or other channels to show attributes, to the use of layering and separation. These rules are accompanied by illustrative examples. We also provide a concise set of references and additional resources for each rule.'),
(89957, 2019, 'plos', 'On measuring selection in cancer from subclonal mutation frequencies', 'Bozic, Ivana|Paterson, Chay|Waclaw, Bartlomiej', 'Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.|Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.|School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom.', 'United States|United States|United Kingdom', 2, '-', 'Journal Article', '10.1371/journal.pcbi.1007368', '31557163', 'Recently available cancer sequencing data have revealed a complex view of the cancer genome containing a multitude of mutations, including drivers responsible for cancer progression and neutral passengers. Measuring selection in cancer and distinguishing drivers from passengers have important implications for development of novel treatment strategies. It has recently been argued that a third of cancers are evolving neutrally, as their mutational frequency spectrum follows a 1/f power law expected from neutral evolution in a particular intermediate frequency range. We study a stochastic model of cancer evolution and derive a formula for the probability distribution of the cancer cell frequency of a subclonal driver, demonstrating that driver frequency is biased towards 0 and 1. We show that it is difficult to capture a driver mutation at an intermediate frequency, and thus the calling of neutrality due to a lack of such driver will significantly overestimate the number of neutrally evolving tumors. Our approach provides precise quantification of the validity of the 1/f statistic across the entire range of all relevant parameter values. We also show that our conclusions remain valid for non-exponential models: spatial 3d model and sigmoidal growth, relevant for early- and late stages of cancer growth.'),
(89958, 2019, 'plos', 'Computational modelling predicts substantial carbon assimilation gains for C3 plants with a single-celled C4 biochemical pump', 'Jurixc4x87, Ivan|Hibberd, Julian M|Blatt, Mike|Burroughs, Nigel J', 'Warwick Systems Biology Centre, University of Warwick, Coventry, United Kingdom.|Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.|Laboratory of Plant Physiology and Biophysics, University of Glasgow, Glasgow, United Kingdom.|Warwick Systems Biology Centre, University of Warwick, Coventry, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007373', '31568503', 'Achieving global food security for the estimated 9 billion people by 2050 is a major scientific challenge. Crop productivity is fundamentally restricted by the rate of fixation of atmospheric carbon. The dedicated enzyme, RubisCO, has a low turnover and poor specificity for CO2. This limitation of C3 photosynthesis (the basic carbon-assimilation pathway present in all plants) is alleviated in some lineages by use of carbon-concentrating-mechanisms, such as the C4 cycle-a biochemical pump that concentrates CO2 near RubisCO increasing assimilation efficacy. Most crops use only C3 photosynthesis, so one promising research strategy to boost their productivity focuses on introducing a C4 cycle. The simplest proposal is to use the cycle to concentrate CO2 inside individual chloroplasts. The photosynthetic efficiency would then depend on the leakage of CO2 out of a chloroplast. We examine this proposal with a 3D spatial model of carbon and oxygen diffusion and C4 photosynthetic biochemistry inside a typical C3-plant mesophyll cell geometry. We find that the cost-efficiency of C4 photosynthesis depends on the gas permeability of the chloroplast envelope, the C4 pathway having higher quantum efficiency than C3 for permeabilities below 300 xcexbcm/s. However, at higher permeabilities the C4 pathway still provides a substantial boost to carbon assimilation with only a moderate decrease in efficiency. The gains would be capped by the ability of chloroplasts to harvest light, but even under realistic light regimes a 100% boost to carbon assimilation is possible. This could be achieved in conjunction with lower investment in chloroplasts if their cell surface coverage is also reduced. Incorporation of this C4 cycle into C3 crops could thus promote higher growth rates and better drought resistance in dry, high-sunlight climates.'),
(89959, 2019, 'plos', 'Telescope: Characterization of the retrotranscriptome by accurate estimation of transposable element expression', 'Bendall, Matthew L|de Mulder, Miguel|Iñiguez, Luis Pedro|Lecanda-Sánchez, Aarón|Pérez-Losada, Marcos|Ostrowski, Mario A|Jones, R Brad|Mulder, Lubbertus C F|Reyes-Terán, Gustavo|Crandall, Keith A|Ormsby, Christopher E|Nixon, Douglas F', 'Computational Biology Institute, Milken Institute School of Public Health, George Washington University, Washington, D.C., United States of America.|Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, N.Y., United States of America.|Center for Research in Infectious Diseases (CIENI), Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico.|Center for Research in Infectious Diseases (CIENI), Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico.|Computational Biology Institute, Milken Institute School of Public Health, George Washington University, Washington, D.C., United States of America.|Department of Immunology, University of Toronto, Toronto, Ontario, Canada.|Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, N.Y., United States of America.|Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Center for Research in Infectious Diseases (CIENI), Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico.|Computational Biology Institute, Milken Institute School of Public Health, George Washington University, Washington, D.C., United States of America.|Center for Research in Infectious Diseases (CIENI), Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico.|Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, N.Y., United States of America.', 'United States|United States|Mexico|Mexico|United States|Canada|United States|United States|Mexico|Un', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006453', '31568525', 'Characterization of Human Endogenous Retrovirus (HERV) expression within the transcriptomic landscape using RNA-seq is complicated by uncertainty in fragment assignment because of sequence similarity. We present Telescope, a computational software tool that provides accurate estimation of transposable element expression (retrotranscriptome) resolved to specific genomic locations. Telescope directly addresses uncertainty in fragment assignment by reassigning ambiguously mapped fragments to the most probable source transcript as determined within a Bayesian statistical model. We demonstrate the utility of our approach through single locus analysis of HERV expression in 13 ENCODE cell types. When examined at this resolution, we find that the magnitude and breadth of the retrotranscriptome can be vastly different among cell types. Furthermore, our approach is robust to differences in sequencing technology, and demonstrates that the retrotranscriptome has potential to be used for cell type identification. We compared our tool with other approaches for quantifying TE expression, and found that Telescope has the greatest resolution, as it estimates expression at specific TE insertions rather than at the TE subfamily level. Telescope performs highly accurate quantification of the retrotranscriptomic landscape in RNA-seq experiments, revealing a differential complexity in the transposable element biology of complex systems not previously observed. Telescope is available at https://github.com/mlbendall/telescope.'),
(89960, 2019, 'plos', 'LOTUS: A single- and multitask machine learning algorithm for the prediction of cancer driver genes', 'Collier, Olivier|Stoven, Véronique|Vert, Jean-Philippe', 'ModalX, UPL, Univ Paris Nanterre, F-92000 Nanterre, France.|MINES ParisTech, PSL University, CBIO-Centre for Computational Biology, F-75006 Paris, France.|MINES ParisTech, PSL University, CBIO-Centre for Computational Biology, F-75006 Paris, France.', 'France|France|France', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007381', '31568528', 'Cancer driver genes, i.e., oncogenes and tumor suppressor genes, are involved in the acquisition of important functions in tumors, providing a selective growth advantage, allowing uncontrolled proliferation and avoiding apoptosis. It is therefore important to identify these driver genes, both for the fundamental understanding of cancer and to help finding new therapeutic targets or biomarkers. Although the most frequently mutated driver genes have been identified, it is believed that many more remain to be discovered, particularly for driver genes specific to some cancer types. In this paper, we propose a new computational method called LOTUS to predict new driver genes. LOTUS is a machine-learning based approach which allows to integrate various types of data in a versatile manner, including information about gene mutations and protein-protein interactions. In addition, LOTUS can predict cancer driver genes in a pan-cancer setting as well as for specific cancer types, using a multitask learning strategy to share information across cancer types. We empirically show that LOTUS outperforms five other state-of-the-art driver gene prediction methods, both in terms of intrinsic consistency and prediction accuracy, and provide predictions of new cancer genes across many cancer types.'),
(89961, 2019, 'plos', 'Estimating influenza incidence using search query deceptiveness and generalized ridge regression', 'Priedhorsky, Reid|Daughton, Ashlynn R|Barnard, Martha|OConnell, Fiona|Osthus, Dave', 'Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Minnetonka Public Schools, Minnetonka, Minnesota, United States of America.|Minnetonka Public Schools, Minnetonka, Minnesota, United States of America.|Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.', 'Mexico|Mexico|United States|United States|Mexico', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007165', '31574086', 'Seasonal influenza is a sometimes surprisingly impactful disease, causing thousands of deaths per year along with much additional morbidity. Timely knowledge of the outbreak state is valuable for managing an effective response. The current state of the art is to gather this knowledge using in-person patient contact. While accurate, this is time-consuming and expensive. This has motivated inquiry into new approaches using internet activity traces, based on the theory that lay observations of health status lead to informative features in internet data. These approaches risk being deceived by activity traces having a coincidental, rather than informative, relationship to disease incidence, to our knowledge, this risk has not yet been quantitatively explored. We evaluated both simulated and real activity traces of varying deceptiveness for influenza incidence estimation using linear regression. We found that deceptiveness knowledge does reduce error in such estimates, that it may help automatically-selected features perform as well or better than features that require human curation, and that a semantic distance measure derived from the Wikipedia article category tree serves as a useful proxy for deceptiveness. This suggests that disease incidence estimation models should incorporate not only data about how internet features map to incidence but also additional data to estimate feature deceptiveness. By doing so, we may gain one more step along the path to accurate, reliable disease incidence estimation using internet data. This capability would improve public health by decreasing the cost and increasing the timeliness of such estimates.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89962, 2019, 'plos', 'Evolving generalists in switching rugged landscapes', 'Wang, Shenshen|Dai, Lei', 'Department of Physics and Astronomy, University of California, Los Angeles, Los Angeles, California, United States of America.|Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.', 'United States|China', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007320', '31574088', 'Evolving systems, be it an antibody repertoire in the face of mutating pathogens or a microbial population exposed to varied antibiotics, constantly search for adaptive solutions in time-varying fitness landscapes. Generalists refer to genotypes that remain fit across diverse selective pressures, while multi-drug resistant microbes are undesired yet prevalent, broadly-neutralizing antibodies are much wanted but rare. However, little is known about under what conditions such generalists with a high capacity to adapt can be efficiently discovered by evolution. In addition, can epistasis-the source of landscape ruggedness and path constraints-play a different role, if the environment varies in a non-random way? We present a generative model to estimate the propensity of evolving generalists in rugged landscapes that are tunably related and alternating relatively slowly. We find that environmental cycling can substantially facilitate the search for fit generalists by dynamically enlarging their effective basins of attraction. Importantly, these high performers are most likely to emerge at intermediate levels of ruggedness and environmental relatedness. Our approach allows one to estimate correlations across environments from the topography of experimental fitness landscapes. Our work provides a conceptual framework to study evolution in time-correlated complex environments, and offers statistical understanding that suggests general strategies for eliciting broadly neutralizing antibodies or preventing microbes from evolving multi-drug resistance.'),
(89963, 2019, 'plos', 'Correction: A unifying Bayesian account of contextual effects in value-based choice', 'Rigoli, Francesco|Mathys, Christoph|Friston, Karl J|Dolan, Raymond J', 'Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.|Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.|Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.|Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.', 'China|China|China|China', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1007366', '31577793', '[This corrects the article DOI: 10.1371/journal.pcbi.1005769.].'),
(89964, 2019, 'plos', 'Ten simple rules for providing optimal administrative support to research teams', 'Garrido, Romina|Trowbridge, Casandra A|Tamura, Nana', 'Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain.|Department of Genetics, Stanford School of Medicine, Stanford University, Stanford, California, United States of America.|RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.', 'Spain|United States|Japan', 0, '-', 'Editorial', '10.1371/journal.pcbi.1007292', '31581228', '-'),
(89965, 2019, 'plos', 'Competition-driven evolution of organismal complexity', 'Ispolatov, Iaroslav|Alekseeva, Evgeniia|Doebeli, Michael', 'Departamento de Fisica, Universidad de Santiago de Chile, Santiago, Chile.|Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.|Department of Zoology and Department of Mathematics, University of British Columbia, Vancouver B.C. Canada.', 'Chile|-|Canada', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007388', '31581239', 'Non-uniform rates of morphological evolution and evolutionary increases in organismal complexity, captured in metaphors like adaptive zones, punctuated equilibrium and blunderbuss patterns, require more elaborate explanations than a simple gradual accumulation of mutations. Here we argue that non-uniform evolutionary increases in phenotypic complexity can be caused by a threshold-like response to growing ecological pressures resulting from evolutionary diversification at a given level of complexity. Acquisition of a new phenotypic feature allows an evolving species to escape this pressure but can typically be expected to carry significant physiological costs. Therefore, the ecological pressure should exceed a certain level to make such an acquisition evolutionarily successful. We present a detailed quantitative description of this process using a microevolutionary competition model as an example. The model exhibits sequential increases in phenotypic complexity driven by diversification at existing levels of complexity and a resulting increase in competitive pressure, which can push an evolving species over the barrier of physiological costs of new phenotypic features.'),
(89966, 2019, 'plos', 'Constrained inference in sparse coding reproduces contextual effects and predicts laminar neural dynamics', 'Capparelli, Federica|Pawelzik, Klaus|Ernst, Udo', 'Institute for Theoretical Physics, University of Bremen, Bremen, Germany.|Institute for Theoretical Physics, University of Bremen, Bremen, Germany.|Institute for Theoretical Physics, University of Bremen, Bremen, Germany.', 'Germany|Germany|Germany', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1007370', '31581240', 'When probed with complex stimuli that extend beyond their classical receptive field, neurons in primary visual cortex display complex and non-linear response characteristics. Sparse coding models reproduce some of the observed contextual effects, but still fail to provide a satisfactory explanation in terms of realistic neural structures and cortical mechanisms, since the connection scheme they propose consists only of interactions among neurons with overlapping input fields. Here we propose an extended generative model for visual scenes that includes spatial dependencies among different features. We derive a neurophysiologically realistic inference scheme under the constraint that neurons have direct access only to local image information. The scheme can be interpreted as a network in primary visual cortex where two neural populations are organized in different layers within orientation hypercolumns that are connected by local, short-range and long-range recurrent interactions. When trained with natural images, the model predicts a connectivity structure linking neurons with similar orientation preferences matching the typical patterns found for long-ranging horizontal axons and feedback projections in visual cortex. Subjected to contextual stimuli typically used in empirical studies, our model replicates several hallmark effects of contextual processing and predicts characteristic differences for surround modulation between the two model populations. In summary, our model provides a novel framework for contextual processing in the visual system proposing a well-defined functional role for horizontal axons and feedback projections.'),
(89967, 2019, 'plos', 'A computational model of postprandial adipose tissue lipid metabolism derived using human arteriovenous stable isotope tracer data', 'ODonovan, Shauna D|Lenz, Michael|Vink, Roel G|Roumans, Nadia J T|de Kok, Theo M C M|Mariman, Edwin C M|Peeters, Ralf L M|van Riel, Natal A W|van Baak, Marleen A|Arts, Ilja C W', 'Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands.|Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands.|Dept. Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands.|Dept. Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands.|Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands.|Dept. Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands.|Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands.|Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands.|Dept. Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands.|Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Neth', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007400', '31581241', 'Given the association of disturbances in non-esterified fatty acid (NEFA) metabolism with the development of Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease, computational models of glucose-insulin dynamics have been extended to account for the interplay with NEFA. In this study, we use arteriovenous measurement across the subcutaneous adipose tissue during a mixed meal challenge test to evaluate the performance and underlying assumptions of three existing models of adipose tissue metabolism and construct a new, refined model of adipose tissue metabolism. Our model introduces new terms, explicitly accounting for the conversion of glucose to glyceraldehye-3-phosphate, the postprandial influx of glycerol into the adipose tissue, and several physiologically relevant delays in insulin signalling in order to better describe the measured adipose tissues fluxes. We then applied our refined model to human adipose tissue flux data collected before and after a diet intervention as part of the Yoyo study, to quantify the effects of caloric restriction on postprandial adipose tissue metabolism. Significant increases were observed in the model parameters describing the rate of uptake and release of both glycerol and NEFA. Additionally, decreases in the models delay in insulin signalling parameters indicates there is an improvement in adipose tissue insulin sensitivity following caloric restriction.'),
(89968, 2019, 'plos', 'Using text-mined trait data to test for cooperate-and-radiate co-evolution between ants and plants', 'Kaur, Katrina M|Malé, Pierre-Jean G|Spence, Erik|Gomez, Crisanto|Frederickson, Megan E', 'Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada.|Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada.|SciNet Consortium, University of Toronto, Toronto, Ontario, Canada.|Departament Ciències Ambientals, Universitat de Girona, Girona, Spain.|Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada.', 'Canada|Canada|Canada|Spain|Canada', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1007323', '31581264', 'Mutualisms may be key innovations that spur lineage diversification by augmenting niche breadth, geographic range, or population size, thereby increasing speciation rates or decreasing extinction rates. Whether mutualism accelerates diversification in both interacting lineages is an open question. Research suggests that plants that attract ant mutualists have higher diversification rates than non-ant associated lineages. We ask whether the reciprocal is true: does the interaction between ants and plants also accelerate diversification in ants, i.e. do ants and plants cooperate-and-radiate? We used a novel text-mining approach to determine which ant species associate with plants in defensive or seed dispersal mutualisms. We investigated patterns of lineage diversification across a recent ant phylogeny using BiSSE, BAMM, and HiSSE models. Ants that associate mutualistically with plants had elevated diversification rates compared to non-mutualistic ants in the BiSSE model, with a similar trend in BAMM, suggesting ants and plants cooperate-and-radiate. However, the best-fitting model was a HiSSE model with a hidden state, meaning that diversification models that do not account for unmeasured traits are inappropriate to assess the relationship between mutualism and ant diversification. Against a backdrop of diversification rate heterogeneity, the best-fitting HiSSE model found that mutualism actually decreases diversification: mutualism evolved much more frequently in rapidly diversifying ant lineages, but then subsequently slowed diversification. Thus, it appears that ant lineages first radiated, then cooperated with plants.'),
(89969, 2000, 'bmc', 'Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions', 'Edwards, J S|Palsson, B O', 'Department of Bioengineering, University of California, San Diego La Jolla, CA 92093-0412, USA. jedwards@arep.med.harvard.edu|Department of Bioengineering, University of California, San Diego La Jolla, CA 92093-0412, USA. jedwards@arep.med.harvard.edu', 'United States|United States', 0, 'Computational Biology|Escherichia coli|Gene Deletion|Genes, Bacterial|Genes, Essential|Genotype|Models, Biological|Phenotype', 'Journal Article', '10.1186/1471-2105-1-1', '11001586', 'Genome sequencing and bioinformatics are producing detailed lists of the molecular components contained in many prokaryotic organisms. From this parts catalogue of a microbial cell, in silico representations of integrated metabolic functions can be constructed and analyzed using flux balance analysis (FBA). FBA is particularly well-suited to study metabolic networks based on genomic, biochemical, and strain specific information.'),
(89970, 2001, 'bmc', 'An algorithm for mapping positively selected members of quasispecies-type viruses', 'Stewart, J J|Watts, P|Litwin, S', 'BioGenetic Ventures, 1100 Olive Way, Suite 300, Seattle, WA 98101 jjs@alumni.princeton.edu|BioGenetic Ventures, 1100 Olive Way, Suite 300, Seattle, WA 98101 jjs@alumni.princeton.edu|BioGenetic Ventures, 1100 Olive Way, Suite 300, Seattle, WA 98101 jjs@alumni.princeton.edu', '-|-|-', 198, 'Algorithms|Amino Acid Sequence|Codon|Computational Biology|Epitope Mapping|Genetic Variation|HIV Envelope Protein gp120|HIV-1|Hemagglutinins, Viral|Influenza A virus|Molecular Sequence Data|Software|Species Specificity', 'Journal Article', '10.1186/1471-2105-1-1', '11265061', 'Many RNA viruses do not have a single, representative genome but instead form a set of related variants that has been called a quasispecies. The sequence variability of such viruses presents a significant bioinformatics challenge. In order for the sequence information to be understood, the complete mutational spectrum needs to be distilled to a biologically relevant and analyzable representation.'),
(89971, 2001, 'bmc', 'mRNA:guanine-N7 cap methyltransferases: identification of novel members of the family, evolutionary analysis, homology modeling, and analysis of sequence-structure-function relationships', 'Bujnicki, J M|Feder, M|Radlinska, M|Rychlewski, L', 'Bioinformatics Laboratory, International Institute of Cell and Molecular Biology, ul, ks, Trojdena 4, 02-109 Warsaw, Poland. iamb@bioinfo.pl|Bioinformatics Laboratory, International Institute of Cell and Molecular Biology, ul, ks, Trojdena 4, 02-109 Warsaw, Poland. iamb@bioinfo.pl|Bioinformatics Laboratory, International Institute of Cell and Molecular Biology, ul, ks, Trojdena 4, 02-109 Warsaw, Poland. iamb@bioinfo.pl|Bioinformatics Laboratory, International Institute of Cell and Molecular Biology, ul, ks, Trojdena 4, 02-109 Warsaw, Poland. iamb@bioinfo.pl', 'Poland|Poland|Poland|Poland', 0, 'Amino Acid Motifs|Amino Acid Sequence|Animals|Binding Sites|Computational Biology|Conserved Sequence|Databases, Protein|Evolution, Molecular|Giardia lamblia|Guanine|Humans|Methyltransferases|Models, Molecular|Molecular Sequence Data|Multigene Family|Mutagenesis, Site-Directed|Phylogeny|Protein Structure, Quaternary|Protozoan Proteins|RNA Caps|Saccharomyces cerevisiae Proteins|Structure-Activity Relationship', 'Comparative Study', '10.1186/1471-2105-1-1', '11472630', 'The 5-terminal cap structure plays an important role in many aspects of mRNA metabolism. Capping enzymes encoded by viruses and pathogenic fungi are attractive targets for specific inhibitors. There is a large body of experimental data on viral and cellular methyltransferases (MTases) that carry out guanine-N7 (cap 0) methylation, including results of extensive mutagenesis. However, a crystal structure is not available and cap 0 MTases are too diverged from other MTases of known structure to allow straightforward homology-based interpretation of these data.'),
(89972, 2001, 'bmc', 'Support vector machines for predicting protein structural class', 'Cai, Y D|Liu, X J|Xu, X|Zhou, G P', 'Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai, 200233, China. y.cai@umist.ac.uk|Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai, 200233, China. y.cai@umist.ac.uk|Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai, 200233, China. y.cai@umist.ac.uk|Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai, 200233, China. y.cai@umist.ac.uk', 'China|China|China|China', 198, 'Algorithms|Computational Biology|Computer Graphics|Databases, Protein|Neural Networks (Computer)|Predictive Value of Tests|Protein Structure, Tertiary|Proteins', 'Comparative Study', '10.1186/1471-2105-1-1', '11483157', 'We apply a new machine learning method, the so-called Support Vector Machine method, to predict the protein structural class. Support Vector Machine method is performed based on the database derived from SCOP, in which protein domains are classified based on known structures and the evolutionary relationships and the principles that govern their 3-D structure.'),
(89973, 2001, 'bmc', 'The relationship between the L1 and L2 domains of the insulin and epidermal growth factor receptors and leucine-rich repeat modules', 'Ward, C W|Garrett, T P', 'CSIRO Health Sciences and Nutrition, 343 Royal Parade Parkville, Victoria 3052, Australia. Colin.Ward@hsn.csiro.au|CSIRO Health Sciences and Nutrition, 343 Royal Parade Parkville, Victoria 3052, Australia. Colin.Ward@hsn.csiro.au', 'Australia|Australia', 0, 'Amino Acid Sequence|Animals|Arabidopsis Proteins|Cattle|Chickens|Computational Biology|Conserved Sequence|ErbB Receptors|Humans|Isoleucine|Leucine|Mice|Molecular Sequence Data|Phenylalanine|Protein Structure, Tertiary|Rabbits|Rats|Receptor, Insulin|Repetitive Sequences, Amino Acid|Sequence Alignment|Valine', 'Comparative Study', '10.1186/1471-2105-1-1', '11504559', 'Leucine-rich repeats are one of the more common modules found in proteins. The leucine-rich repeat consensus motif is LxxLxLxxNxLxxLxxLxxLxx- where the first 11-12 residues are highly conserved and the remainder of the repeat can vary in size Leucine-rich repeat proteins have been subdivided into seven subfamilies, none of which include members of the epidermal growth factor receptor or insulin receptor families despite the similarity between the 3D structure of the L domains of the type I insulin-like growth factor receptor and some leucine-rich repeat proteins.'),
(89974, 2001, 'bmc', 'A study of quality measures for protein threading models', 'Cristobal, S|Zemla, A|Fischer, D|Rychlewski, L|Elofsson, A', 'Cell and Molecular Biology Department, Box 596. BMC Uppsala University, SE-751 24 Uppsala, Sweden. susana.cristobal@icm.uu.se|Cell and Molecular Biology Department, Box 596. BMC Uppsala University, SE-751 24 Uppsala, Sweden. susana.cristobal@icm.uu.se|Cell and Molecular Biology Department, Box 596. BMC Uppsala University, SE-751 24 Uppsala, Sweden. susana.cristobal@icm.uu.se|Cell and Molecular Biology Department, Box 596. BMC Uppsala University, SE-751 24 Uppsala, Sweden. susana.cristobal@icm.uu.se|Cell and Molecular Biology Department, Box 596. BMC Uppsala University, SE-751 24 Uppsala, Sweden. susana.cristobal@icm.uu.se', 'Sweden|Sweden|Sweden|Sweden|Sweden', 0, 'Computational Biology|Models, Molecular|Predictive Value of Tests|Protein Conformation|Protein Structure, Tertiary', 'Comparative Study', '10.1186/1471-2105-1-1', '11545673', 'Prediction of protein structures is one of the fundamental challenges in biology today. To fully understand how well different prediction methods perform, it is necessary to use measures that evaluate their performance. Every two years, starting in 1994, the CASP (Critical Assessment of protein Structure Prediction) process has been organized to evaluate the ability of different predictors to blindly predict the structure of proteins. To capture different features of the models, several measures have been developed during the CASP processes. However, these measures have not been examined in detail before. In an attempt to develop fully automatic measures that can be used in CASP, as well as in other type of benchmarking experiments, we have compared twenty-one measures. These measures include the measures used in CASP3 and CASP2 as well as have measures introduced later. We have studied their ability to distinguish between the better and worse models submitted to CASP3 and the correlation between them.'),
(89975, 2001, 'bmc', 'FOUNTAIN: a JAVA open-source package to assist large sequencing projects', 'Buerstedde, J M|Prill, F', 'Department of Cellular Immunology, Heinrich-Pette-Institute, Martinistr 52, 20251 Hamburg, Germany. buersted@genetics.hpi.uni-hamburg.de|Department of Cellular Immunology, Heinrich-Pette-Institute, Martinistr 52, 20251 Hamburg, Germany. buersted@genetics.hpi.uni-hamburg.de', 'Germany|Germany', 198, 'Algorithms|Computer Graphics|Databases, Genetic|Forecasting|Internet|Multigene Family|Polymorphism, Genetic|Programming Languages|Sequence Analysis, DNA|Software Design|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-1-1', '11591214', 'Better automation, lower cost per reaction and a heightened interest in comparative genomics has led to a dramatic increase in DNA sequencing activities. Although the large sequencing projects of specialized centers are supported by in-house bioinformatics groups, many smaller laboratories face difficulties managing the appropriate processing and storage of their sequencing output. The challenges include documentation of clones, templates and sequencing reactions, and the storage, annotation and analysis of the large number of generated sequences.'),
(89976, 2001, 'bmc', 'The distributed annotation system', 'Dowell, R D|Jokerst, R M|Day, A|Eddy, S R|Stein, L', 'Howard Hughes Medical Institute and Department of Genetics, Washington University, St. Louis, MO 63110 USA. robin@genetics.wustl.edu|Howard Hughes Medical Institute and Department of Genetics, Washington University, St. Louis, MO 63110 USA. robin@genetics.wustl.edu|Howard Hughes Medical Institute and Department of Genetics, Washington University, St. Louis, MO 63110 USA. robin@genetics.wustl.edu|Howard Hughes Medical Institute and Department of Genetics, Washington University, St. Louis, MO 63110 USA. robin@genetics.wustl.edu|Howard Hughes Medical Institute and Department of Genetics, Washington University, St. Louis, MO 63110 USA. robin@genetics.wustl.edu', 'United States|United States|United States|United States|United States', 0, 'Base Sequence|Computational Biology|Computer Terminals|Databases, Genetic|Genome, Human|Humans|Internet|Reference Values|Software', 'Journal Article', '10.1186/1471-2105-1-1', '11667947', 'Currently, most genome annotation is curated by centralized groups with limited resources. Efforts to share annotations transparently among multiple groups have not yet been satisfactory.'),
(89977, 2001, 'bmc', 'FastGroup: a program to dereplicate libraries of 16S rDNA sequences', 'Seguritan, V|Rohwer, F', 'Department of Computational Science San Diego State, University San Diego, California, 92182, USA. vsegurit@pacbell.net|Department of Computational Science San Diego State, University San Diego, California, 92182, USA. vsegurit@pacbell.net', 'United States|United States', 0, 'Algorithms|Cluster Analysis|Computational Biology|DNA, Bacterial|Gene Library|Genes, rRNA|Programming Languages|RNA, Bacterial|RNA, Ribosomal, 16S|Sequence Alignment|Software', 'Comparative Study', '10.1186/1471-2105-1-1', '11707150', 'Ribosomal 16S DNA sequences are an essential tool for identifying and classifying microbes. High-throughput DNA sequencing now makes it economically possible to produce very large datasets of 16S rDNA sequences in short time periods, necessitating new computer tools for analyses. Here we describe FastGroup, a Java program designed to dereplicate libraries of 16S rDNA sequences. By dereplication we mean to: 1) compare all the sequences in a data set to each other, 2) group similar sequences together, and 3) output a representative sequence from each group. In this way, duplicate sequences are removed from a library.'),
(89978, 2001, 'bmc', 'Noncoding RNA gene detection using comparative sequence analysis', 'Rivas, E|Eddy, S R', 'Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine, Saint Louis, Missouri, USA. elena@genetics.wustl.edu|Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine, Saint Louis, Missouri, USA. elena@genetics.wustl.edu', 'United States|United States', 198, 'Algorithms|Animals|Base Sequence|Bayes Theorem|Caenorhabditis|Caenorhabditis elegans|Computational Biology|Computer Simulation|Escherichia coli|Genome|Genome, Bacterial|Models, Genetic|Molecular Sequence Data|RNA, Bacterial|RNA, Helminth|RNA, Untranslated|Salmonella typhi|Sensitivity and Specificity|Sequence Analysis, RNA', 'Comparative Study', '10.1186/1471-2105-1-1', '11801179', 'Noncoding RNA genes produce transcripts that exert their function without ever producing proteins. Noncoding RNA gene sequences do not have strong statistical signals, unlike protein coding genes. A reliable general purpose computational genefinder for noncoding RNA genes has been elusive.'),
(89979, 2002, 'bmc', 'Identification and characterization of subfamily-specific signatures in a large protein superfamily by a hidden Markov model approach', 'Truong, Kevin|Ikura, Mitsuhiko', 'Division of Molecular and Structural Biology, Ontario Cancer Institute and Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. ktruong@uhnres.utoronto.ca|Division of Molecular and Structural Biology, Ontario Cancer Institute and Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. ktruong@uhnres.utoronto.ca', 'Canada|Canada', 0, 'Binding Sites|Cadherins|Calcium-Binding Proteins|Computational Biology|Databases, Protein|EF Hand Motifs|Markov Chains|Models, Genetic|Parvalbumins|Proteins|Proteome|Proteomics|Quantitative Structure-Activity Relationship|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-1-1', '11818024', 'Most profile and motif databases strive to classify protein sequences into a broad spectrum of protein families. The next step of such database studies should include the development of classification systems capable of distinguishing between subfamilies within a structurally and functionally diverse superfamily. This would be helpful in elucidating sequence-structure-function relationships of proteins.'),
(89980, 2002, 'bmc', 'Match-only integral distribution (MOID) algorithm for high-density oligonucleotide array analysis', 'Zhou, Yingyao|Abagyan, Ruben', 'Genomics Institute of the Novartis Research Foundation, 3115 Merryfield Row, San Diego, CA 92121, USA. zhou@gnf.org|Genomics Institute of the Novartis Research Foundation, 3115 Merryfield Row, San Diego, CA 92121, USA. zhou@gnf.org', 'United States|United States', 198, 'Algorithms|Computational Biology|Computer Simulation|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes', 'Comparative Study', '10.1186/1471-2105-1-1', '11835687', 'High-density oligonucleotide arrays have become a valuable tool for high-throughput gene expression profiling. Increasing the array information density and improving the analysis algorithms are two important computational research topics.'),
(89981, 2002, 'bmc', 'The comparative RNA web (CRW) site: an online database of comparative sequence and structure information for ribosomal, intron, and other RNAs', 'Cannone, Jamie J|Subramanian, Sankar|Schnare, Murray N|Collett, James R|DSouza, Lisa M|Du, Yushi|Feng, Brian|Lin, Nan|Madabusi, Lakshmi V|Müller, Kirsten M|Pande, Nupur|Shang, Zhidi|Yu, Nan|Gutell, Robin R', 'Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu|Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu|Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu|Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu|Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu|Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu|Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu|Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu|Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu|Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu|Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu|Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu|Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu|Institute for Cellular and Molecular Biology, Section of Integrative Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712-1095, USA. cannone@mail.utexas.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Base Sequence|Databases, Nucleic Acid|Internet|Molecular Sequence Data|Nucleic Acid Conformation|RNA|RNA, Archaeal|RNA, Bacterial|RNA, Ribosomal, 16S|RNA, Ribosomal, 23S|RNA, Ribosomal, 5S|RNA, Transfer', 'Comparative Study', '10.1186/1471-2105-1-1', '11869452', 'Comparative analysis of RNA sequences is the basis for the detailed and accurate predictions of RNA structure and the determination of phylogenetic relationships for organisms that span the entire phylogenetic tree. Underlying these accomplishments are very large, well-organized, and processed collections of RNA sequences. This data, starting with the sequences organized into a database management system and aligned to reveal their higher-order structure, and patterns of conservation and variation for organisms that span the phylogenetic tree, has been collected and analyzed. This type of information can be fundamental for and have an influence on the study of phylogenetic relationships, RNA structure, and the melding of these two fields.'),
(89982, 2002, 'bmc', 'Correlating overrepresented upstream motifs to gene expression: a computational approach to regulatory element discovery in eukaryotes', 'Caselle, Michele|Di Cunto, Ferdinando|Provero, Paolo', 'Dipartimento di Fisica Teorica, Università di Torino, and INFN, Sezione di Torino, Torino, Italy. caselle@to.infn.it|Dipartimento di Fisica Teorica, Università di Torino, and INFN, Sezione di Torino, Torino, Italy. caselle@to.infn.it|Dipartimento di Fisica Teorica, Università di Torino, and INFN, Sezione di Torino, Torino, Italy. caselle@to.infn.it', 'Italy|Italy|Italy', 0, '5 Flanking Region|Base Composition|Computational Biology|DNA-Binding Proteins|Eukaryotic Cells|False Positive Reactions|Fungal Proteins|Gene Expression Regulation, Fungal|Genes, Fungal|Genes, Regulator|Genome, Fungal|Open Reading Frames|Repressor Proteins|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Homology, Nucleic Acid|Transcription Factors', 'Comparative Study', '10.1186/1471-2105-1-1', '11876822', 'Gene regulation in eukaryotes is mainly effected through transcription factors binding to rather short recognition motifs generally located upstream of the coding region. We present a novel computational method to identify regulatory elements in the upstream region of eukaryotic genes. The genes are grouped in sets sharing an overrepresented short motif in their upstream sequence. For each set, the average expression level from a microarray experiment is determined: If this level is significantly higher or lower than the average taken over the whole genome, then the overerpresented motif shared by the genes in the set is likely to play a role in their regulation.'),
(89983, 2002, 'bmc', 'Re-annotation of genome microbial coding-sequences: finding new genes and inaccurately annotated genes', 'Bocs, Stéphanie|Danchin, Antoine|Médigue, Claudine', 'Laboratoire Génome et Informatique, Université de Versailles, 91034 Evry Cedex, France. scbocs@infobiogen.fr|Laboratoire Génome et Informatique, Université de Versailles, 91034 Evry Cedex, France. scbocs@infobiogen.fr|Laboratoire Génome et Informatique, Université de Versailles, 91034 Evry Cedex, France. scbocs@infobiogen.fr', 'France|France|France', 198, 'Computational Biology|Databases, Protein|Gene Transfer, Horizontal|Genes, Archaeal|Genes, Bacterial|Genetic Variation|Genome, Archaeal|Genome, Bacterial|Gram-Negative Bacteria|Gram-Positive Bacteria|Open Reading Frames|Predictive Value of Tests|Reading Frames|Software|Spirochaetaceae', 'Journal Article', '10.1186/1471-2105-1-1', '11879526', 'Analysis of any newly sequenced bacterial genome starts with the identification of protein-coding genes. Despite the accumulation of multiple complete genome sequences, which provide useful comparisons with close relatives among other organisms during the annotation process, accurate gene prediction remains quite difficult. A major reason for this situation is that genes are tightly packed in prokaryotes, resulting in frequent overlap. Thus, detection of translation initiation sites and/or selection of the correct coding regions remain difficult unless appropriate biological knowledge (about the structure of a gene) is imbedded in the approach.'),
(89984, 2002, 'bmc', 'tacg--a grep for DNA', 'Mangalam, Harry J', 'tacg Informatics, 1 Whistler Ct, Irvine, CA, 92612, USA. hjm@tacgi.com', 'United States', 0, 'Algorithms|Base Composition|Computational Biology|DNA|Fuzzy Logic|Software', 'Journal Article', '10.1186/1471-2105-1-1', '11882250', 'Pattern matching is the core of bioinformatics, it is used in database searching, restriction enzyme mapping, and finding open reading frames. It is done repeatedly over increasingly long sequences, thus codes must be efficient and insensitive to sequence length. Such patterns of interest include simple motifs with IUPAC degeneracies, regular expressions, patterns allowing mismatches, and probability matrices.'),
(89985, 2002, 'bmc', 'An algorithm and program for finding sequence specific oligonucleotide probes for species identification', 'Pozhitkov, Alexander E|Tautz, Diethard', 'University of Cologne, Institute of Genetics, AG Tautz, Weyertal 121, D-50931 Cologne, Germany. alex.pozhitkov@uni-koeln.de|University of Cologne, Institute of Genetics, AG Tautz, Weyertal 121, D-50931 Cologne, Germany. alex.pozhitkov@uni-koeln.de', 'Germany|Germany', 0, 'Algorithms|Computational Biology|Cupriavidus necator|Databases, Genetic|Gammaproteobacteria|Oligonucleotide Probes|RNA, Bacterial|RNA, Ribosomal, 18S|RNA, Ribosomal, 28S|Software Design|Species Specificity|Sulfolobus|Thermotoga maritima|Treponema', 'Comparative Study', '10.1186/1471-2105-1-1', '11882251', 'The identification of species or species groups with specific oligo-nucleotides as molecular signatures is becoming increasingly popular for bacterial samples. However, it shows also great promise for other small organisms that are taxonomically difficult to tract.'),
(89986, 2002, 'bmc', 'Universal sequence map (USM) of arbitrary discrete sequences', 'Almeida, Jonas S|Vinga, Susana', 'Dept Biometry & Epidemiology, Medical Univ South Carolina, 135 Cannon street, Suite 303, PO Box 250835, Charleston, SC 29425, USA. almeidaj@musc.edu|Dept Biometry & Epidemiology, Medical Univ South Carolina, 135 Cannon street, Suite 303, PO Box 250835, Charleston, SC 29425, USA. almeidaj@musc.edu', 'United States|United States', 0, 'Algorithms|Computational Biology|Markov Chains|Models, Genetic|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Comparative Study', '10.1186/1471-2105-1-1', '11895567', 'For over a decade the idea of representing biological sequences in a continuous coordinate space has maintained its appeal but not been fully realized. The basic idea is that any sequence of symbols may define trajectories in the continuous space conserving all its statistical properties. Ideally, such a representation would allow scale independent sequence analysis--without the context of fixed memory length. A simple example would consist on being able to infer the homology between two sequences solely by comparing the coordinates of any two homologous units.'),
(89987, 2002, 'bmc', 'RNA:(guanine-N2) methyltransferases RsmC/RsmD and their homologs revisited--bioinformatic analysis and prediction of the active site based on the uncharacterized Mj0882 protein structure', 'Bujnicki, Janusz M|Rychlewski, Leszek', 'Bioinformatics Laboratory, International Institute of Cell and Molecular Biology, ul, ks, Trojdena 4, 02-109 Warsaw, Poland. iamb@wp.pl|Bioinformatics Laboratory, International Institute of Cell and Molecular Biology, ul, ks, Trojdena 4, 02-109 Warsaw, Poland. iamb@wp.pl', 'Poland|Poland', 0, 'Archaeal Proteins|Binding Sites|Computational Biology|Crystallography, X-Ray|Escherichia coli Proteins|Evolution, Molecular|Guanine|Methanococcus|Methyltransferases|Models, Molecular|Molecular Structure|Predictive Value of Tests|Protein Folding|Protein Structure, Tertiary|Sequence Alignment|Sequence Homology, Nucleic Acid|tRNA Methyltransferases', 'Comparative Study', '10.1186/1471-2105-1-1', '11929612', 'Escherichia coli guanine-N2 (m2G) methyltransferases (MTases) RsmC and RsmD modify nucleosides G1207 and G966 of 16S rRNA. They possess a common MTase domain in the C-terminus and a variable region in the N-terminus. Their C-terminal domain is related to the YbiN family of hypothetical MTases, but nothing is known about the structure or function of the N-terminal domain.'),
(89988, 2002, 'bmc', 'Sources of variability and effect of experimental approach on expression profiling data interpretation', 'Bakay, Marina|Chen, Yi-Wen|Borup, Rehannah|Zhao, Po|Nagaraju, Kanneboyina|Hoffman, Eric P', 'Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Avenue, NW Washington, DC 20010 USA. mbakay@cnmc.org|Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Avenue, NW Washington, DC 20010 USA. mbakay@cnmc.org|Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Avenue, NW Washington, DC 20010 USA. mbakay@cnmc.org|Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Avenue, NW Washington, DC 20010 USA. mbakay@cnmc.org|Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Avenue, NW Washington, DC 20010 USA. mbakay@cnmc.org|Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Avenue, NW Washington, DC 20010 USA. mbakay@cnmc.org', 'United States|United States|United States|United States|United States|United States', 0, 'Animals|Cell Line|Child|Child, Preschool|Computational Biology|Data Interpretation, Statistical|Dystrophin|Female|Gene Expression Profiling|Genetic Variation|Humans|Male|Mice|Mice, Mutant Strains|Muscles|Muscular Dystrophy, Duchenne|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|RNA|Sensitivity and Specificity|Spleen', 'Journal Article', '10.1186/1471-2105-1-1', '11936955', 'We provide a systematic study of the sources of variability in expression profiling data using 56 RNAs isolated from human muscle biopsies (34 Affymetrix MuscleChip arrays), and 36 murine cell culture and tissue RNAs (42 Affymetrix U74Av2 arrays).'),
(89989, 2002, 'bmc', 'Homology induction: the use of machine learning to improve sequence similarity searches', 'Karwath, Andreas|King, Ross D', 'Department of Computer Sciences, University of Wales, Aberystwyth, SY23 3DB, UK. adk@aber.ac.uk|Department of Computer Sciences, University of Wales, Aberystwyth, SY23 3DB, UK. adk@aber.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Artificial Intelligence|Computational Biology|Databases, Protein|Fungal Proteins|Internet|Mice|Oryza|Plant Proteins|Predictive Value of Tests|Retroviridae Proteins|Sensitivity and Specificity|Sequence Alignment|Sequence Homology, Amino Acid', 'Comparative Study', '10.1186/1471-2105-1-1', '11972320', 'The inference of homology between proteins is a key problem in molecular biology The current best approaches only identify approximately 50% of homologies (with a false positive rate set at 1/1000).'),
(89990, 2002, 'bmc', 'CoreGenes: a computational tool for identifying and cataloging core genes in a set of small genomes', 'Zafar, Nikhat|Mazumder, Raja|Seto, Donald', 'School of Computational Sciences, George Mason University, 10900 University Boulevard, MSN 4E3, Manassas, VA 20110 USA. nikhatzafar@yahoo.com|School of Computational Sciences, George Mason University, 10900 University Boulevard, MSN 4E3, Manassas, VA 20110 USA. nikhatzafar@yahoo.com|School of Computational Sciences, George Mason University, 10900 University Boulevard, MSN 4E3, Manassas, VA 20110 USA. nikhatzafar@yahoo.com', 'United States|United States|United States', 0, 'Algorithms|Chloroplasts|Computational Biology|Databases, Genetic|Genes|Genes, Essential|Genes, Plant|Genes, Viral|Genome|Genome, Plant|Genome, Viral|Genomics|Internet|Mitochondria|Programming Languages|Software|Software Design|Software Validation|Viral Structural Proteins', 'Comparative Study', '10.1186/1471-2105-1-1', '11972896', 'Improvements in DNA sequencing technology and methodology have led to the rapid expansion of databases comprising DNA sequence, gene and genome data. Lower operational costs and heightened interest resulting from initial intriguing novel discoveries from genomics are also contributing to the accumulation of these data sets. A major challenge is to analyze and to mine data from these databases, especially whole genomes. There is a need for computational tools that look globally at genomes for data mining.'),
(89991, 2002, 'bmc', 'NBLAST: a cluster variant of BLAST for NxN comparisons', 'Dumontier, Michel|Hogue, Christopher W V', 'Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada M5S 1A8. micheld@mshri.on.ca|Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada M5S 1A8. micheld@mshri.on.ca', 'Canada|Canada', 0, 'Algorithms|Cluster Analysis|Computational Biology|Database Management Systems|Genetic Variation|Sequence Alignment', 'Comparative Study', '10.1186/1471-2105-1-1', '12019022', 'The BLAST algorithm compares biological sequences to one another in order to determine shared motifs and common ancestry. However, the comparison of all non-redundant (NR) sequences against all other NR sequences is a computationally intensive task. We developed NBLAST as a cluster computer implementation of the BLAST family of sequence comparison programs for the purpose of generating pre-computed BLAST alignments and neighbour lists of NR sequences.'),
(89992, 2002, 'bmc', 'RIO: analyzing proteomes by automated phylogenomics using resampled inference of orthologs', 'Zmasek, Christian M|Eddy, Sean R', 'Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine, St Louis, MO 63110, USA. zmasek@genetics.wustl.edu|Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine, St Louis, MO 63110, USA. zmasek@genetics.wustl.edu', 'United States|United States', 198, 'Animals|Arabidopsis|Arabidopsis Proteins|Caenorhabditis elegans|Caenorhabditis elegans Proteins|Computational Biology|Databases, Protein|Evolution, Molecular|Genes, Duplicate|Genome|Genome, Plant|Genomics|L-Lactate Dehydrogenase|Malate Dehydrogenase|Models, Genetic|Phylogeny|Proteome|Sequence Homology, Amino Acid', 'Comparative Study', '10.1186/1471-2105-1-1', '12028595', 'When analyzing protein sequences using sequence similarity searches, orthologous sequences (that diverged by speciation) are more reliable predictors of a new proteins function than paralogous sequences (that diverged by gene duplication). The utility of phylogenetic information in high-throughput genome annotation (phylogenomics) is widely recognized, but existing approaches are either manual or not explicitly based on phylogenetic trees.'),
(89993, 2002, 'bmc', 'Identifying functional relationships among human genes by systematic analysis of biological literature', 'Tao, Yong-Chuan|Leibel, Rudolph L', 'Life Science Informatics Unit, Functional Genomics Area, Novartis Pharmaceuticals, Summit, NJ 07901, USA. yong-chuan.tao@pharma.novartis.com|Life Science Informatics Unit, Functional Genomics Area, Novartis Pharmaceuticals, Summit, NJ 07901, USA. yong-chuan.tao@pharma.novartis.com', 'United States|United States', 0, 'Apoptosis|Computational Biology|Genes|Humans', 'Journal Article', '10.1186/1471-2105-1-1', '12067419', 'The availability of biomedical literature in electronic format has made it possible to implement automatic text processing methods to expose implicit relationships among different documents, and more importantly, the functional relationships among the molecules and processes that these documents describe.'),
(89994, 2002, 'bmc', 'A memory-efficient dynamic programming algorithm for optimal alignment of a sequence to an RNA secondary structure', 'Eddy, Sean R', 'Howard Hughes Medical Institute & Department of Genetics, Washington University School of Medicine, Saint Louis, Missouri 63110 USA. eddy@genetics.wustl.edu', 'United States', 198, 'Algorithms|Computational Biology|Consensus Sequence|Empirical Research|Markov Chains|Models, Statistical|Nucleic Acid Conformation|Programming, Linear|RNA|RNA, Ribosomal|RNA, Small Cytoplasmic|RNA, Transfer|Sequence Alignment|Signal Recognition Particle|Software|Software Design|Time Factors', 'Comparative Study', '10.1186/1471-2105-1-1', '12095421', 'Covariance models (CMs) are probabilistic models of RNA secondary structure, analogous to profile hidden Markov models of linear sequence. The dynamic programming algorithm for aligning a CM to an RNA sequence of length N is O(N3) in memory. This is only practical for small RNAs.');
