INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(95975, 2013, 'bmc', 'Transcript features alone enable accurate prediction and understanding of gene expression in S cerevisiae', 'Zur, Hadas|Tuller, Tamir', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada', 0, '3 Untranslated Regions|5 Untranslated Regions|Fungal Proteins|Gene Expression|Gene Expression Regulation, Fungal|Nonlinear Dynamics|Protein Biosynthesis|RNA, Messenger|Saccharomyces cerevisiae|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-14-S15-S1', '24564391', 'Gene expression is a central process in all living organisms. Central questions in the field are related to the way the expression levels of genes are encoded in the transcripts and affect their evolution, and the potential to predict expression levels solely by transcript features. In this study we analyze S. cerevisiae, a model organism with the most abundant relevant cellular and genomic measurements, to evaluate the accuracy in which expression levels can be predicted by different parts of the transcript. To this end, we perform various types of regression analyses based on a total of 5323 features of the transcript. The main advantage of the proposed predictors over previous ones is related to the accurate and comprehensive definitions of the relevant transcript features, which are based on biophysical knowledge of the gene transcription and translation processes, their modeling and evolution.'),
(95976, 2014, 'bmc', 'Reducing bias in RNA sequencing data: a novel approach to compute counts', 'Finotello, Francesca|Lavezzo, Enrico|Bianco, Luca|Barzon, Luisa|Mazzon, Paolo|Fontana, Paolo|Toppo, Stefano|Di Camillo, Barbara', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 21, 'Base Composition|Gene Expression Regulation|High-Throughput Nucleotide Sequencing|Humans|RNA|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-15-S1-S7', '24564404', 'In the last decade, Next-Generation Sequencing technologies have been extensively applied to quantitative transcriptomics, making RNA sequencing a valuable alternative to microarrays for measuring and comparing gene transcription levels. Although several methods have been proposed to provide an unbiased estimate of transcript abundances through data normalization, all of them are based on an initial count of the total number of reads mapping on each transcript. This procedure, in principle robust to random noise, is actually error-prone if reads are not uniformly distributed along sequences, as happens indeed due to sequencing errors and ambiguity in read mapping. Here we propose a new approach, called maxcounts, to quantify the expression assigned to an exon as the maximum of its per-base counts, and we assess its performance in comparison with the standard approach described above, which considers the total number of reads aligned to an exon. The two measures are compared using multiple data sets and considering several evaluation criteria: independence from gene-specific covariates, such as exon length and GC-content, accuracy and precision in the quantification of true concentrations and robustness of measurements to variations of alignments quality.'),
(95977, 2013, 'bmc', 'Visual cavity analysis in molecular simulations', 'Parulek, Julius|Turkay, Cagatay|Reuter, Nathalie|Viola, Ivan', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Amino Acids|Binding Sites|Computational Biology|Computer Graphics|Humans|Ligands|Models, Molecular|Molecular Docking Simulation|Myeloblastin|Protein Structure, Tertiary', 'Journal Article', '10.1186/1471-2105-14-S19-S4', '24564409', 'Molecular surfaces provide a useful mean for analyzing interactions between biomolecules, such as identification and characterization of ligand binding sites to a host macromolecule. We present a novel technique, which extracts potential binding sites, represented by cavities, and characterize them by 3D graphs and by amino acids. The binding sites are extracted using an implicit function sampling and graph algorithms. We propose an advanced cavity exploration technique based on the graph parameters and associated amino acids. Additionally, we interactively visualize the graphs in the context of the molecular surface. We apply our method to the analysis of MD simulations of Proteinase 3, where we verify the previously described cavities and suggest a new potential cavity to be studied. '),
(95978, 2013, 'bmc', 'Structural analysis on mutation residues and interfacial water molecules for human TIM disease understanding', 'Li, Zhenhua|He, Ying|Liu, Qian|Zhao, Liang|Wong, Limsoon|Kwoh, Chee Keong|Nguyen, Hung|Li, Jinyan', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 6, 'Amino Acid Sequence|Anemia, Hemolytic, Congenital Nonspherocytic|Animals|Carbohydrate Metabolism, Inborn Errors|Humans|Molecular Dynamics Simulation|Molecular Sequence Data|Mutation|Protein Structure, Tertiary|Sequence Alignment|Software|Triose-Phosphate Isomerase|Water', 'Journal Article', '10.1186/1471-2105-14-S16-S11', '24564410', 'Human triosephosphate isomerase (HsTIM) deficiency is a genetic disease caused often by the pathogenic mutation E104D. This mutation, located at the side of an abnormally large cluster of water in the inter-subunit interface, reduces the thermostability of the enzyme. Why and how these water molecules are directly related to the excessive thermolability of the mutant have not been investigated in structural biology.'),
(95979, 2013, 'bmc', 'Genome-wide probabilistic reconciliation analysis across vertebrates', 'Mahmudi, Owais|Sjöstrand, Joel|Sennblad, Bengt|Lagergren, Jens', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Animals|Bayes Theorem|Evolution, Molecular|Gene Duplication|Genome|Humans|Phylogeny|Vertebrates', 'Journal Article', '10.1186/1471-2105-14-S15-S10', '24564421', 'Gene duplication is considered to be a major driving force in evolution that enables the genome of a species to acquire new functions. A reconciliation--a mapping of gene tree vertices to the edges or vertices of a species tree--explains where gene duplications have occurred on the species tree. In this study, we sample reconciliations from a posterior over reconciliations, gene trees, edge lengths and other parameters, given a species tree and gene sequences. We employ a Bayesian analysis tool, based on the probabilistic model DLRS that integrates gene duplication, gene loss and sequence evolution under a relaxed molecular clock for substitution rates, to obtain this posterior.'),
(95980, 2013, 'bmc', 'Exploring cavity dynamics in biomolecular systems', 'Lindow, Norbert|Baum, Daniel|Bondar, Ana-Nicoleta|Hege, Hans-Christian', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Bacteriorhodopsins|Computational Biology|Computer Graphics|Models, Molecular|Molecular Dynamics Simulation|Protein Conformation|Proteins', 'Journal Article', '10.1186/1471-2105-14-S19-S5', '24564434', 'The internal cavities of proteins are dynamic structures and their dynamics may be associated with conformational changes which are required for the functioning of the protein. In order to study the dynamics of these internal protein cavities, appropriate tools are required that allow rapid identification of the cavities as well as assessment of their time-dependent structures.'),
(95981, 2013, 'bmc', 'HCS-Neurons: identifying phenotypic changes in multi-neuron images upon drug treatments of high-content screening', 'Charoenkwan, Phasit|Hwang, Eric|Cutler, Robert W|Lee, Hua-Chin|Ko, Li-Wei|Huang, Hui-Ling|Ho, Shinn-Ying', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Animals|Cell Line|Electronic Data Processing|High-Throughput Screening Assays|Image Processing, Computer-Assisted|Mice|Neurites|Neurons|Nocodazole|Phenotype|Regression Analysis|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-14-S16-S12', '24564437', 'High-content screening (HCS) has become a powerful tool for drug discovery. However, the discovery of drugs targeting neurons is still hampered by the inability to accurately identify and quantify the phenotypic changes of multiple neurons in a single image (named multi-neuron image) of a high-content screen. Therefore, it is desirable to develop an automated image analysis method for analyzing multi-neuron images.'),
(95982, 2014, 'bmc', 'AnnotateGenomicRegions: a web application', 'Zammataro, Luca|DeMolfetta, Rita|Bucci, Gabriele|Ceol, Arnaud|Muller, Heiko', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada', 0, 'Animals|Genome|Genomics|Humans|Internet|Mice|Saccharomyces cerevisiae|Software|Zebrafish', 'Journal Article', '10.1186/1471-2105-15-S1-S8', '24564446', 'Modern genomic technologies produce large amounts of data that can be mapped to specific regions in the genome. Among the first steps in interpreting the results is annotation of genomic regions with known features such as genes, promoters, CpG islands etc. Several tools have been published to perform this task. However, using these tools often requires a significant amount of bioinformatics skills and/or downloading and installing dedicated software.'),
(95983, 2013, 'bmc', 'In silico experimental evolution: a tool to test evolutionary scenarios', 'Batut, Bérénice|Parsons, David P|Fischer, Stephan|Beslon, Guillaume|Knibbe, Carole', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada', 0, 'Base Sequence|Buchnera|Escherichia coli|Evolution, Molecular|Genome|Genomics|Prochlorococcus|Selection, Genetic', 'Journal Article', '10.1186/1471-2105-14-S15-S11', '24564457', 'Comparative genomics has revealed that some species have exceptional genomes, compared to their closest relatives. For instance, some species have undergone a strong reduction of their genome with a drastic reduction of their genic repertoire. Deciphering the causes of these atypical trajectories can be very difficult because of the many phenomena that are intertwined during their evolution (e.g. changes of population size, environment structure and dynamics, selection strength, mutation rates...). Here we propose a methodology based on synthetic experiments to test the individual effect of these phenomena on a population of simulated organisms. We developed an evolutionary model--aevol--in which evolutionary conditions can be changed one at a time to test their effects on genome size and organization (e.g. coding ratio). To illustrate the proposed approach, we used aevol to test the effects of a strong reduction in the selection strength on a population of (simulated) bacteria. Our results show that this reduction of selection strength leads to a genome reduction of ~35% with a slight loss of coding sequences (~15% of the genes are lost--mainly those for which the contribution to fitness is the lowest). More surprisingly, under a low selection strength, genomes undergo a strong reduction of the noncoding compartment (~55% of the noncoding sequences being lost). These results are consistent with what is observed in reduced Prochlorococcus strains (marine cyanobacteria) when compared to close relatives.'),
(95984, 2013, 'bmc', 'The looks of an odour--visualising neural odour response patterns in real time', 'Strauch, Martin|Müthing, Clemens|Broeg, Marc P|Szyszka, Paul|Münch, Daniel|Laudes, Thomas|Deussen, Oliver|Galizia, Cosmas Giovanni|Merhof, Dorit', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Animals|Arthropod Antennae|Bees|Brain|Calcium|Drosophila melanogaster|Female|Fluorescent Dyes|Image Interpretation, Computer-Assisted|Neuroimaging|Neurons|Odorants|Olfactory Perception|Software', 'Journal Article', '10.1186/1471-2105-14-S19-S6', '24564474', 'Calcium imaging in insects reveals the neural response to odours, both at the receptor level on the antenna and in the antennal lobe, the first stage of olfactory information processing in the brain. Changes of intracellular calcium concentration in response to odour presentations can be observed by employing calcium-sensitive, fluorescent dyes. The response pattern across all recorded units is characteristic for the odour.'),
(95985, 2013, 'bmc', 'MetaSel: a metaphase selection tool using a Gaussian-based classification technique', 'Uttamatanin, Ravi|Yuvapoositanon, Peerapol|Intarapanich, Apichart|Kaewkamnerd, Saowaluck|Phuksaritanon, Ratsapan|Assawamakin, Anunchai|Tongsima, Sissades', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Chromosomes|Humans|Image Processing, Computer-Assisted|Karyotyping|Metaphase|Models, Statistical|Normal Distribution|Software', 'Journal Article', '10.1186/1471-2105-14-S16-S13', '24564477', 'Identification of good metaphase spreads is an important step in chromosome analysis for identifying individuals with genetic disorders. The process of finding suitable metaphase chromosomes for accurate clinical analysis is, however, very time consuming since they are selected manually. The selection of suitable metaphase chromosome spreads thus represents a major bottleneck for conventional cytogenetic analysis. Although many algorithms have been developed for karyotyping, none have adequately addressed the critical bottleneck of selecting suitable chromosome spreads. In this paper, we present a software tool that uses a simple rule-based system to efficiently identify metaphase spreads suitable for karyotyping.'),
(95986, 2014, 'bmc', 'Toolboxes for a standardised and systematic study of glycans', 'Campbell, Matthew P|Ranzinger, René|Lütteke, Thomas|Mariethoz, Julien|Hayes, Catherine A|Zhang, Jingyu|Akune, Yukie|Aoki-Kinoshita, Kiyoko F|Damerell, David|Carta, Giorgio|York, Will S|Haslam, Stuart M|Narimatsu, Hisashi|Rudd, Pauline M|Karlsson, Niclas G|Packer, Nicolle H|Lisacek, Frédérique', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Ca', 0, 'Carbohydrate Sequence|Glycomics|Internet|Polysaccharides|Proteins|Software', 'Journal Article', '10.1186/1471-2105-15-S1-S9', '24564482', 'Recent progress in method development for characterising the branched structures of complex carbohydrates has now enabled higher throughput technology. Automation of structure analysis then calls for software development since adding meaning to large data collections in reasonable time requires corresponding bioinformatics methods and tools. Current glycobioinformatics resources do cover information on the structure and function of glycans, their interaction with proteins or their enzymatic synthesis. However, this information is partial, scattered and often difficult to find to for non-glycobiologists.'),
(95987, 2014, 'bmc', 'Eureka-DMA: an easy-to-operate graphical user interface for fast comprehensive investigation and analysis of DNA microarray data', 'Abelson, Sagi', 'The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.', 'Israel', 1, 'Algorithms|Animals|Computational Biology|Databases, Genetic|Humans|Mice|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-15-53', '24564491', 'In the past decade, the field of molecular biology has become increasingly quantitative, rapid development of new technologies enables researchers to investigate and address fundamental issues quickly and in an efficient manner which were once impossible. Among these technologies, DNA microarray provides methodology for many applications such as gene discovery, diseases diagnosis, drug development and toxicological research and it has been used increasingly since it first emerged. Multiple tools have been developed to interpret the high-throughput data produced by microarrays. However, many times, less consideration has been given to the fact that an extensive and effective interpretation requires close interplay between the bioinformaticians who analyze the data and the biologists who generate it. To bridge this gap and to simplify the usability of such tools we developed Eureka-DMA - an easy-to-operate graphical user interface that allows bioinformaticians and bench-biologists alike to initiate analyses as well as to investigate the data produced by DNA microarrays.'),
(95988, 2013, 'bmc', 'RMaNI: Regulatory Module Network Inference framework', 'Madhamshettiwar, Piyush B|Maetschke, Stefan R|Davis, Melissa J|Ragan, Mark A', 'The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.|The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.|The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.|The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.', 'Israel|Israel|Israel|Israel', 6, 'Carcinoma, Hepatocellular|Cluster Analysis|Computational Biology|Gene Expression|Gene Regulatory Networks|Humans|Internet|Liver Neoplasms|Systems Biology', 'Journal Article', '10.1186/1471-2105-14-S16-S14', '24564496', 'Cell survival and development are orchestrated by complex interlocking programs of gene activation and repression. Understanding how this gene regulatory network (GRN) functions in normal states, and is altered in cancers subtypes, offers fundamental insight into oncogenesis and disease progression, and holds great promise for guiding clinical decisions. Inferring a GRN from empirical microarray gene expression data is a challenging task in cancer systems biology. In recent years, module-based approaches for GRN inference have been proposed to address this challenge. Despite the demonstrated success of module-based approaches in uncovering biologically meaningful regulatory interactions, their application remains limited a single condition, without supporting the comparison of multiple disease subtypes/conditions. Also, their use remains unnecessarily restricted to computational biologists, as accurate inference of modules and their regulators requires integration of diverse tools and heterogeneous data sources, which in turn requires scripting skills, data infrastructure and powerful computational facilities. New analytical frameworks are required to make module-based GRN inference approach more generally useful to the research community.'),
(95989, 2014, 'bmc', 'Automatic classification of protein structures using low-dimensional structure space mappings', 'Asarnow, Daniel|Singh, Rahul', 'The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.|The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.', 'Israel|Israel', 1, 'Algorithms|Cluster Analysis|Computational Biology|Databases, Protein|Protein Conformation|Proteins', 'Journal Article', '10.1186/1471-2105-15-S2-S1', '24564500', 'Protein function is closely intertwined with protein structure. Discovery of meaningful structure-function relationships is of utmost importance in protein biochemistry and has led to creation of high-quality, manually curated classification databases, such as the gold-standard SCOP (Structural Classification of Proteins) database. The SCOP database and its counterparts such as CATH provide a detailed and comprehensive description of the structural and evolutionary relationships of the proteins of known structure and are widely employed in structural and computational biology. Since manual classification is both subjective and highly laborious, automated classification of novel structures is increasingly an active area of research. The design of methods for automated structure classification has been rendered even more important since the recent past, due to the explosion in number of solved structures arising out of various structural biology initiatives. In this paper we propose an approach to the problem of structure classification based on creating and tessellating low dimensional maps of the protein structure space (MPSS). Given a set of protein structures, an MPSS is a low dimensional embedding of structural similarity-based distances between the molecules. In an MPSS, a group of proteins (such as all the proteins in the PDB or sub-samplings thereof) under consideration are represented as point clouds and structural relatedness maps to spatial adjacency of the points. In this paper we present methods and results that show that MPSS can be used to create tessellations of the protein space comparable to the clade systems within SCOP. Though we have used SCOP as the gold standard, the proposed approach is equally applicable for other structural classifications.'),
(95990, 2013, 'bmc', 'Quantitative synteny scoring improves homology inference and partitioning of gene families', 'Ali, Raja Hashim|Muhammad, Sayyed|Khan, Mehmood|Arvestad, Lars', 'The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.|The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.|The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.|The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.', 'Israel|Israel|Israel|Israel', 0, 'Algorithms|Animals|Base Sequence|Chromosome Mapping|Cluster Analysis|Humans|Mice|Proteins|Sequence Homology, Nucleic Acid|Synteny', 'Journal Article', '10.1186/1471-2105-14-S15-S12', '24564516', 'Clustering sequences into families has long been an important step in characterization of genes and proteins. There are many algorithms developed for this purpose, most of which are based on either direct similarity between gene pairs or some sort of network structure, where weights on edges of constructed graphs are based on similarity. However, conserved synteny is an important signal that can help distinguish homology and it has not been utilized to its fullest potential.'),
(95991, 2013, 'bmc', 'Incorporating substrate sequence motifs and spatial amino acid composition to identify kinase-specific phosphorylation sites on protein three-dimensional structures', 'Su, Min-Gang|Lee, Tzong-Yi', 'The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.|The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.', 'Israel|Israel', 0, 'Amino Acid Sequence|Amino Acids|Databases, Protein|Internet|Models, Molecular|Phosphorylation|Phosphotransferases|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-14-S16-S2', '24564522', 'Protein phosphorylation catalyzed by kinases plays crucial regulatory roles in cellular processes. Given the high-throughput mass spectrometry-based experiments, the desire to annotate the catalytic kinases for in vivo phosphorylation sites has motivated. Thus, a variety of computational methods have been developed for performing a large-scale prediction of kinase-specific phosphorylation sites. However, most of the proposed methods solely rely on the local amino acid sequences surrounding the phosphorylation sites. An increasing number of three-dimensional structures make it possible to physically investigate the structural environment of phosphorylation sites.'),
(95992, 2014, 'bmc', 'FISH Amyloid - a new method for finding amyloidogenic segments in proteins based on site specific co-occurrence of aminoacids', 'Gasior, Pawel|Kotulska, Malgorzata', 'The Ruth and Bruce Rappaport Faculty of Medicine, Haifa, Technion, Israel. sagi.abelson@gmail.com.|Institute of Biomedical Engineering and Instrumentation, Wroclaw University of Technology, 50-370 Wroclaw, Poland. malgorzata.kotulska@pwr.wroc.pl.', 'Israel|Poland', 0, 'Algorithms|Amino Acid Sequence|Amino Acids|Amyloid|Artificial Intelligence|Computational Biology|Peptides|ROC Curve|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-15-54', '24564523', 'Amyloids are proteins capable of forming fibrils whose intramolecular contact sites assume densely packed zipper pattern. Their oligomers can underlie serious diseases, e.g. Alzheimers and Parkinsons diseases. Recent studies show that short segments of aminoacids can be responsible for amyloidogenic properties of a protein. A few hundreds of such peptides have been experimentally found but experimental testing of all candidates is currently not feasible. Here we propose an original machine learning method for classification of aminoacid sequences, based on discovering a segment with a discriminative pattern of site-specific co-occurrences between sequence elements. The pattern is based on the positions of residues with correlated occurrence over a sliding window of a specified length. The algorithm first recognizes the most relevant training segment in each positive training instance. Then the classification is based on maximal distances between co-occurrence matrix of the relevant segments in positive training sequences and the matrix from negative training segments. The method was applied for studying sequences of aminoacids with regard to their amyloidogenic properties.'),
(95993, 2014, 'bmc', 'Transcriptional regulation prediction of antiestrogen resistance in breast cancer based on RNA polymerase II binding data', 'Zhang, Denan|Wang, Guohua|Wang, Yadong', 'Institute of Biomedical Engineering and Instrumentation, Wroclaw University of Technology, 50-370 Wroclaw, Poland. malgorzata.kotulska@pwr.wroc.pl.|Institute of Biomedical Engineering and Instrumentation, Wroclaw University of Technology, 50-370 Wroclaw, Poland. malgorzata.kotulska@pwr.wroc.pl.|Institute of Biomedical Engineering and Instrumentation, Wroclaw University of Technology, 50-370 Wroclaw, Poland. malgorzata.kotulska@pwr.wroc.pl.', 'Poland|Poland|Poland', 3, 'Breast Neoplasms|Drug Resistance, Neoplasm|Estrogen Receptor Modulators|Female|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|MCF-7 Cells|RNA Polymerase II|Signal Transduction|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-15-S2-S10', '24564526', 'Although endocrine therapy impedes estrogen-ER signaling pathway and thus reduces breast cancer mortality, patients remain at continued risk of relapse after tamoxifen or other endocrine therapies. Understanding the mechanisms of endocrine resistance, particularly the role of transcriptional regulation is very important and necessary.'),
(95994, 2013, 'bmc', 'Haploid to diploid alignment for variation calling assessment', 'Mäkinen, Veli|Rahkola, Jani', 'Institute of Biomedical Engineering and Instrumentation, Wroclaw University of Technology, 50-370 Wroclaw, Poland. malgorzata.kotulska@pwr.wroc.pl.|Institute of Biomedical Engineering and Instrumentation, Wroclaw University of Technology, 50-370 Wroclaw, Poland. malgorzata.kotulska@pwr.wroc.pl.', 'Poland|Poland', 0, 'Algorithms|Diploidy|Genome|Haploidy|Humans|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-14-S15-S13', '24564537', 'Variation calling is the process of detecting differences between donor and consensus DNA via high-throughput sequencing read mapping. When evaluating the performance of different variation calling methods, a typical scenario is to simulate artificial (diploid) genomes and sample reads from those. After variation calling, one can then compute precision and recall statistics. This works reliably on SNPs but on larger indels there is the problem of invariance: a predicted deletion/insertion can differ slightly from the true one, yet both make the same change to the genome. Also exactly correct predictions are rare, especially on larger insertions, so one should consider some notion of approximate predictions for fair comparison.'),
(95995, 2014, 'bmc', 'Phenotyping date palm varieties via leaflet cross-sectional imaging and artificial neural network application', 'Arinkin, Vladimir|Digel, Ilya|Porst, Dariusz|Artmann, Aysegül Temiz|Artmann, Gerhard M', 'Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.|Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.|Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.|Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.|Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.', 'Germany|Germany|Germany|Germany|Germany', 2, 'Algorithms|Arecaceae|Image Processing, Computer-Assisted|Microscopy, Fluorescence|Neural Networks (Computer)|Phenotype|Plant Leaves', 'Journal Article', '10.1186/1471-2105-15-55', '24564551', 'True date palms (Phoenix dactylifera L.) are impressive trees and have served as an indispensable source of food for mankind in tropical and subtropical countries for centuries. The aim of this study is to differentiate date palm tree varieties by analysing leaflet cross sections with technical/optical methods and artificial neural networks (ANN).'),
(95996, 2013, 'bmc', 'Pathway-based drug repositioning using causal inference', 'Li, Jiao|Lu, Zhiyong', 'Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.|Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.', 'Germany|Germany', 0, 'Artificial Intelligence|Computational Biology|Computer Simulation|Crohn Disease|Drug Repositioning|Gene Regulatory Networks|Humans|Likelihood Functions|Reproducibility of Results', 'Journal Article', '10.1186/1471-2105-14-S16-S3', '24564553', 'Recent in vivo studies showed new hopes of drug repositioning through causality inference from drugs to disease. Inspired by their success, here we present an in silico method for building a causal network (CauseNet) between drugs and diseases, in an attempt to systematically identify new therapeutic uses of existing drugs.'),
(95997, 2014, 'bmc', 'On the selection of appropriate distances for gene expression data clustering', 'Jaskowiak, Pablo A|Campello, Ricardo J G B|Costa, Ivan G', 'Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.|Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.|Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.', 'Germany|Germany|Germany', 61, 'Cluster Analysis|Gene Expression Profiling|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-15-S2-S2', '24564555', 'Clustering is crucial for gene expression data analysis. As an unsupervised exploratory procedure its results can help researchers to gain insights and formulate new hypothesis about biological data from microarrays. Given different settings of microarray experiments, clustering proves itself as a versatile exploratory tool. It can help to unveil new cancer subtypes or to identify groups of genes that respond similarly to a specific experimental condition. In order to obtain useful clustering results, however, different parameters of the clustering procedure must be properly tuned. Besides the selection of the clustering method itself, determining which distance is going to be employed between data objects is probably one of the most difficult decisions.'),
(95998, 2014, 'bmc', 'Using distances between Top-n-gram and residue pairs for protein remote homology detection', 'Liu, Bin|Xu, Jinghao|Zou, Quan|Xu, Ruifeng|Wang, Xiaolong|Chen, Qingcai', 'Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.|Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.|Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.|Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.|Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.|Institute for Bioengineering (IFB), Aachen University of Applied Sciences, Heinrich-Mussmann-Str, 1, 52428 Juelich, Germany. arinkin.vladimir@yahoo.com.', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Amino Acids|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-15-S2-S3', '24564580', 'Protein remote homology detection is one of the central problems in bioinformatics, which is important for both basic research and practical application. Currently, discriminative methods based on Support Vector Machines (SVMs) achieve the state-of-the-art performance. Exploring feature vectors incorporating the position information of amino acids or other protein building blocks is a key step to improve the performance of the SVM-based methods.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(95999, 2014, 'bmc', 'iview: an interactive WebGL visualizer for protein-ligand complex', 'Li, Hongjian|Leung, Kwong-Sak|Nakane, Takanori|Wong, Man-Hon', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China', 42, 'Computational Biology|Computer Graphics|Internet|Ligands|Molecular Docking Simulation|Protein Binding|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-15-56', '24564583', 'Visualization of protein-ligand complex plays an important role in elaborating protein-ligand interactions and aiding novel drug design. Most existing web visualizers either rely on slow software rendering, or lack virtual reality support. The vital feature of macromolecular surface construction is also unavailable.'),
(96000, 2013, 'bmc', 'cellXpress: a fast and user-friendly software platform for profiling cellular phenotypes', 'Laksameethanasan, Danai|Tan, Rui|Toh, Geraldine|Loo, Lit-Hsin', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China', 16, 'Algorithms|Animals|Cell Line|Cells|Cluster Analysis|Humans|Image Processing, Computer-Assisted|Phenotype|Software', 'Journal Article', '10.1186/1471-2105-14-S16-S4', '24564609', 'High-throughput, image-based screens of cellular responses to genetic or chemical perturbations generate huge numbers of cell images. Automated analysis is required to quantify and compare the effects of these perturbations. However, few of the current freely-available bioimage analysis software tools are optimized for efficient handling of these images. Even fewer of them are designed to transform the phenotypic features measured from these images into discriminative profiles that can reveal biologically meaningful associations among the tested perturbations.'),
(96001, 2013, 'bmc', 'Statistics for approximate gene clusters', 'Jahn, Katharina|Winter, Sascha|Stoye, Jens|Böcker, Sebastian', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China', 0, 'Biometry|Gene Order|Genome, Bacterial|Multigene Family|Probability', 'Journal Article', '10.1186/1471-2105-14-S15-S14', '24564620', 'Genes occurring co-localized in multiple genomes can be strong indicators for either functional constraints on the genome organization or remnant ancestral gene order. The computational detection of these patterns, which are usually referred to as gene clusters, has become increasingly sensitive over the past decade. The most powerful approaches allow for various types of imperfect cluster conservation: Cluster locations may be internally rearranged. The individual cluster locations may contain only a subset of the cluster genes and may be disrupted by uninvolved genes. Moreover cluster locations may not at all occur in some or even most of the studied genomes. The detection of such low quality clusters increases the risk of mistaking faint patterns that occur merely by chance for genuine findings. Therefore, it is crucial to estimate the significance of computational gene cluster predictions and discriminate between true conservation and coincidental clustering.'),
(96002, 2014, 'bmc', 'NETTAB 2012 on Integrated Bio-Search', 'Romano, Paolo|Lisacek, Frédérique|Masseroli, Marco', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China', 2, 'Algorithms|Computational Biology|Genomics|Humans|Periodicals as Topic|Software', 'Congress', '10.1186/1471-2105-15-S1-S1', '24564635', 'The NETTAB 2012 workshop, held in Como on November 14-16, 2012, was devoted to Integrated Bio-Search, that is to technologies, methods, architectures, systems and applications for searching, retrieving, integrating and analyzing data, information, and knowledge with the aim of answering complex bio-medical-molecular questions, i.e. some of the most challenging issues in bioinformatics today. It brought together about 80 researchers working in the field of Bioinformatics, Computational Biology, Biology, Computer Science and Engineering. More than 50 scientific contributions, including keynote and tutorial talks, oral communications, posters and software demonstrations, were presented at the workshop. This preface provides a brief overview of the workshop and shortly introduces the peer-reviewed manuscripts that were accepted for publication in this Supplement. '),
(96003, 2013, 'bmc', 'A computational pipeline for identifying kinetic motifs to aid in the design and improvement of synthetic gene circuits', 'Chiang, Austin W T|Hwang, Ming-Jing', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China', 2, 'Computational Biology|Computer Simulation|Gene Expression|Gene Regulatory Networks|Genes, Synthetic|Kinetics|Models, Statistical|Stochastic Processes|Synthetic Biology', 'Journal Article', '10.1186/1471-2105-14-S16-S5', '24564638', 'An increasing number of genetic components are available in several depositories of such components to facilitate synthetic biology research, but picking out those that will allow a designed circuit to achieve the specified function still requires multiple cycles of testing. Here, we addressed this problem by developing a computational pipeline to mathematically simulate a gene circuit for a comprehensive range and combination of the kinetic parameters of the biological components that constitute the gene circuit.'),
(96004, 2013, 'bmc', 'Disentangling homeologous contigs in allo-tetraploid assembly: application to durum wheat', 'Ranwez, Vincent|Holtz, Yan|Sarah, Gautier|Ardisson, Morgane|Santoni, Sylvain|Glémin, Sylvain|Tavaud-Pirra, Muriel|David, Jacques', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China|China|China|China|China', 12, 'Base Sequence|Diploidy|High-Throughput Nucleotide Sequencing|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Tetraploidy|Triticum', 'Journal Article', '10.1186/1471-2105-14-S15-S15', '24564644', 'Using Next Generation Sequencing, SNP discovery is relatively easy on diploid species and still hampered in polyploid species by the confusion due to homeology. We develop HomeoSplitter, a fast and effective solution to split original contigs obtained by RNAseq into two homeologous sequences. It uses the differential expression of the two homeologous genes in the RNA. We verify that the new sequences are closer to the diploid progenitors of the allopolyploid species than the original contig. By remapping original reads on these new sequences, we also verify that the number of valuable detected SNPs has significantly increased.'),
(96005, 2014, 'bmc', 'Extracting rate changes in transcriptional regulation from MEDLINE abstracts', 'Liu, Wenting|Miao, Kui|Li, Guangxia|Chang, Kuiyu|Zheng, Jie|Rajapakse, Jagath C', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China|China|China', 0, 'Artificial Intelligence|Biological Ontologies|Data Mining|Gene Expression Regulation|Gene Regulatory Networks|Humans|Knowledge Bases|MEDLINE|PubMed|Time Factors|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-15-S2-S4', '24564647', 'Time delays are important factors that are often neglected in gene regulatory network (GRN) inference models. Validating time delays from knowledge bases is a challenge since the vast majority of biological databases do not record temporal information of gene regulations. Biological knowledge and facts on gene regulations are typically extracted from bio-literature with specialized methods that depend on the regulation task. In this paper, we mine evidences for time delays related to the transcriptional regulation of yeast from the PubMed abstracts.'),
(96006, 2013, 'bmc', 'Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes', 'Wang, Yue|Goh, Wilson|Wong, Limsoon|Montana, Giovanni|Alzheimers Disease Neuroimaging Initiative', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China|China', 36, 'Algorithms|Alzheimer Disease|Artificial Intelligence|Brain|Computer Simulation|Genome-Wide Association Study|Humans|Magnetic Resonance Imaging|Neuroimaging|Phenotype|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Software', 'Journal Article', '10.1186/1471-2105-14-S16-S6', '24564704', 'Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive.'),
(96007, 2013, 'bmc', 'Finishing bacterial genome assemblies with Mix', 'Soueidan, Hayssam|Maurier, Florence|Groppi, Alexis|Sirand-Pugnet, Pascal|Tardy, Florence|Citti, Christine|Dupuy, Virginie|Nikolski, Macha', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China|China|China|China|China', 0, 'Algorithms|Genome, Bacterial|High-Throughput Nucleotide Sequencing|Mycoplasma|Sequence Analysis, DNA|Software Design', 'Journal Article', '10.1186/1471-2105-14-S15-S16', '24564706', 'Among challenges that hamper reaping the benefits of genome assembly are both unfinished assemblies and the ensuing experimental costs. First, numerous software solutions for genome de novo assembly are available, each having its advantages and drawbacks, without clear guidelines as to how to choose among them. Second, these solutions produce draft assemblies that often require a resource intensive finishing phase.'),
(96008, 2014, 'bmc', 'Towards integrative gene functional similarity measurement', 'Peng, Jiajie|Wang, Yadong|Chen, Jin', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China', 26, 'Arabidopsis|Gene Ontology|Genes, Fungal|Genes, Plant|Humans|Saccharomyces cerevisiae|Semantics|Software', 'Journal Article', '10.1186/1471-2105-15-S2-S5', '24564710', 'In Gene Ontology, the Molecular Function (MF) categorization is a widely used knowledge framework for gene function comparison and prediction. Its structure and annotation provide a convenient way to compare gene functional similarities at the molecular level. The existing gene similarity measures, however, solely rely on one or few aspects of MF without utilizing all the rich information available including structure, annotation, common terms, lowest common parents.'),
(96009, 2014, 'bmc', 'A tool for mapping Single Nucleotide Polymorphisms using Graphics Processing Units', 'Manconi, Andrea|Orro, Alessandro|Manca, Emanuele|Armano, Giuliano|Milanesi, Luciano', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China|China', 4, 'Algorithms|Base Sequence|Chromosome Mapping|Chromosomes|Genome, Human|Genome-Wide Association Study|Genotype|Humans|Molecular Sequence Data|Polymorphism, Single Nucleotide|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-15-S1-S10', '24564714', 'Single Nucleotide Polymorphism (SNP) genotyping analysis is very susceptible to SNPs chromosomal position errors. As it is known, SNPs mapping data are provided along the SNP arrays without any necessary information to assess in advance their accuracy. Moreover, these mapping data are related to a given build of a genome and need to be updated when a new build is available. As a consequence, researchers often plan to remap SNPs with the aim to obtain more up-to-date SNPs chromosomal positions. In this work, we present G-SNPM a GPU (Graphics Processing Unit) based tool to map SNPs on a genome.'),
(96010, 2013, 'bmc', 'Structural analysis of the novel influenza A (H7N9) viral Neuraminidase interactions with current approved neuraminidase inhibitors Oseltamivir, Zanamivir, and Peramivir in the presence of mutation R289K', 'Tran-To Su, Chinh|Ouyang, Xuchang|Zheng, Jie|Kwoh, Chee-Keong', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China', 0, 'Antiviral Agents|Cyclopentanes|Drug Resistance, Viral|Enzyme Inhibitors|Guanidines|Influenza A Virus, H7N9 Subtype|Molecular Docking Simulation|Molecular Dynamics Simulation|Mutation|Neuraminidase|Oseltamivir|Viral Proteins|Zanamivir', 'Journal Article', '10.1186/1471-2105-14-S16-S7', '24564719', 'Since late March 2013, there has been another global health concern with a sudden wave of flu infections by a novel strain of avian influenza A (H7N9) virus in China. To-date, there have been more than 100 infections with 23 deaths. It is more worrying as this viral strain has never been detected in humans and only been found to be of low-pathogenicity. Currently, there are 3 effective neuraminidase inhibitors for this H7N9 virus strain, i.e. oseltamivir, zanamivir, and peramivir. These drugs have been used for treatment of the H7N9 influenza in China. However, how these inhibitors work and affect the binding cavity of the novel H7N9 neuraminidase in the presence of potential mutations has not been disclosed. In our study, we investigate steric effects and subsequently show the conformational restraints of the inhibitor-binding site of the non-mutated and mutated H7N9 neuraminidase structures to different drug compounds.'),
(96011, 2013, 'bmc', 'Reconstructing the modular recombination history of Staphylococcus aureus phages', 'Swenson, Krister M|Guertin, Paul|Deschênes, Hugo|Bergeron, Anne', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China', 0, 'Algorithms|Bacteriophages|Genome, Viral|Recombination, Genetic|Sequence Analysis, DNA|Staphylococcus aureus', 'Journal Article', '10.1186/1471-2105-14-S15-S17', '24564731', 'Viruses that infect bacteria, called phages, are well-known for their extreme mosaicism, in which an individual genome shares many different parts with many others. The mechanisms for creating these mosaics are largely unknown but are believed to be recombinations, either illegitimate, or partly homologous. In order to reconstruct the history of these recombinations, we need to identify the positions where recombinations may have occurred, and develop algorithms to generate and explore the possible reconstructions.'),
(96012, 2014, 'bmc', 'The Risa R/Bioconductor package: integrative data analysis from experimental metadata and back again', 'González-Beltrán, Alejandra|Neumann, Steffen|Maguire, Eamonn|Sansone, Susanna-Assunta|Rocca-Serra, Philippe', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China|China', 10, 'Genomics|Mass Spectrometry|Metabolomics|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-15-S1-S11', '24564732', 'The ISA-Tab format and software suite have been developed to break the silo effect induced by technology-specific formats for a variety of data types and to better support experimental metadata tracking. Experimentalists seldom use a single technique to monitor biological signals. Providing a multi-purpose, pragmatic and accessible format that abstracts away common constructs for describing Investigations, Studies and Assays, ISA is increasingly popular. To attract further interest towards the format and extend support to ensure reproducible research and reusable data, we present the Risa package, which delivers a central component to support the ISA format by enabling effortless integration with R, the popular, open source data crunching environment.'),
(96013, 2014, 'bmc', 'Prediction of heterotrimeric protein complexes by two-phase learning using neighboring kernels', 'Ruan, Peiying|Hayashida, Morihiro|Maruyama, Osamu|Akutsu, Tatsuya', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China', 8, 'Discriminant Analysis|Multiprotein Complexes|Protein Multimerization|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-15-S2-S6', '24564744', 'Protein complexes play important roles in biological systems such as gene regulatory networks and metabolic pathways. Most methods for predicting protein complexes try to find protein complexes with size more than three. It, however, is known that protein complexes with smaller sizes occupy a large part of whole complexes for several species. In our previous work, we developed a method with several feature space mappings and the domain composition kernel for prediction of heterodimeric protein complexes, which outperforms existing methods.'),
(96014, 2013, 'bmc', 'Mapping proteins in the presence of paralogs using units of coevolution', 'El-Kebir, Mohammed|Marschall, Tobias|Wohlers, Inken|Patterson, Murray|Heringa, Jaap|Schönhuth, Alexander|Klau, Gunnar W', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China|China|China|China', 0, 'Amino Acid Sequence|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-14-S15-S18', '24564758', 'We study the problem of mapping proteins between two protein families in the presence of paralogs. This problem occurs as a difficult subproblem in coevolution-based computational approaches for protein-protein interaction prediction.'),
(96015, 2014, 'bmc', 'Distilling structure in Taverna scientific workflows: a refactoring approach', 'Cohen-Boulakia, Sarah|Chen, Jiuqiang|Missier, Paolo|Goble, Carole|Williams, Alan R|Froidevaux, Christine', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China|China|China', 8, 'Algorithms|Computational Biology|User-Computer Interface|Workflow', 'Journal Article', '10.1186/1471-2105-15-S1-S12', '24564760', 'Scientific workflows management systems are increasingly used to specify and manage bioinformatics experiments. Their programming model appeals to bioinformaticians, who can use them to easily specify complex data processing pipelines. Such a model is underpinned by a graph structure, where nodes represent bioinformatics tasks and links represent the dataflow. The complexity of such graph structures is increasing over time, with possible impacts on scientific workflows reuse. In this work, we propose effective methods for workflow design, with a focus on the Taverna model. We argue that one of the contributing factors for the difficulties in reuse is the presence of anti-patterns, a term broadly used in program design, to indicate the use of idiomatic forms that lead to over-complicated design. The main contribution of this work is a method for automatically detecting such anti-patterns, and replacing them with different patterns which result in a reduction in the workflows overall structural complexity. Rewriting workflows in this way will be beneficial both in terms of user experience (easier design and maintenance), and in terms of operational efficiency (easier to manage, and sometimes to exploit the latent parallelism amongst the tasks).'),
(96016, 2013, 'bmc', 'Identifying conserved protein complexes between species by constructing interolog networks', 'Nguyen, Phi-Vu|Srihari, Sriganesh|Leong, Hon Wai', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China', 0, 'Computational Biology|Conserved Sequence|Humans|Protein Interaction Mapping|Proteins|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-14-S16-S8', '24564762', 'Protein complexes conserved across species indicate processes that are core to cellular machinery (e.g. cell-cycle or DNA damage-repair complexes conserved across human and yeast). While numerous computational methods have been devised to identify complexes from the protein interaction (PPI) networks of individual species, these are severely limited by noise and errors (false positives) in currently available datasets. Our analysis using human and yeast PPI networks revealed that these methods missed several important complexes including those conserved between the two species (e.g. the MLH1-MSH2-PMS2-PCNA mismatch-repair complex). Here, we note that much of the functionalities of yeast complexes have been conserved in human complexes not only through sequence conservation of proteins but also of critical functional domains. Therefore, integrating information of domain conservation might throw further light on conservation patterns between yeast and human complexes.'),
(96017, 2014, 'bmc', 'Protein folding in HP model on hexagonal lattices with diagonals', 'Shaw, Dipan|Shohidull Islam, A S M|Sohel Rahman, M|Hasan, Masud', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China', 0, 'Algorithms|Computational Biology|Models, Biological|Protein Folding|Protein Structure, Tertiary|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-15-S2-S7', '24564789', 'Three dimensional structure prediction of a protein from its amino acid sequence, known as protein folding, is one of the most studied computational problem in bioinformatics and computational biology. Since, this is a hard problem, a number of simplified models have been proposed in literature to capture the essential properties of this problem. In this paper we introduce the hexagonal lattices with diagonals to handle the protein folding problem considering the well researched HP model. We give two approximation algorithms for protein folding on this lattice. Our first algorithm is a 5/3-approximation algorithm, which is based on the strategy of partitioning the entire protein sequence into two pieces. Our next algorithm is also based on partitioning approaches and improves upon the first algorithm.'),
(96018, 2014, 'bmc', 'QTREDS: a Ruby on Rails-based platform for omics laboratories', 'Palla, Piergiorgio|Frau, Gianfranco|Vargiu, Laura|Rodriguez-Tomé, Patricia', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China', 6, 'Computational Biology|Humans|Information Systems|Internet|Software|User-Computer Interface|Workflow', 'Journal Article', '10.1186/1471-2105-15-S1-S13', '24564791', 'In recent years, the experimental aspects of the laboratory activities have been growing in complexity in terms of amount and diversity of data produced, equipment used, of computer-based workflows needed to process and analyze the raw data generated. To enhance the level of quality control over the laboratory activities and efficiently handle the large amounts of data produced, a Laboratory Management Information System (LIMS) is highly-recommended. A LIMS is a complex software platform that helps researchers to have a complete knowledge of the laboratory activities at each step encouraging them to adopt good laboratory practices.'),
(96019, 2013, 'bmc', 'Agent based modeling of Treg-Teff cross regulation in relapsing-remitting multiple sclerosis', 'Pennisi, Marzio|Rajput, Abdul-Mateen|Toldo, Luca|Pappalardo, Francesco', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China', 0, 'Brain|Genetic Predisposition to Disease|Humans|Models, Biological|Multiple Sclerosis, Relapsing-Remitting|T-Lymphocyte Subsets|T-Lymphocytes, Regulatory', 'Journal Article', '10.1186/1471-2105-14-S16-S9', '24564794', 'Multiple sclerosis (MS) is a disease of central nervous system that causes the removal of fatty myelin sheath from axons of the brain and spinal cord. Autoimmunity plays an important role in this pathology outcome and bodys own immune system attacks on the myelin sheath causing the damage. The etiology of the disease is partially understood and the response to treatment cannot easily be predicted.'),
(96020, 2013, 'bmc', 'The dynamics of functional classes of plant genes in rediploidized ancient polyploids', 'Chen, Eric C H|Buen Abad Najar, Carlos|Zheng, Chunfang|Brandts, Alex|Lyons, Eric|Tang, Haibao|Carretero-Paulet, Lorenzo|Albert, Victor A|Sankoff, David', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China|China|China|China|China|China', 10, 'Evolution, Molecular|Gene Duplication|Genes, Plant|Genome, Plant|Plants|Polyploidy', 'Journal Article', '10.1186/1471-2105-14-S15-S19', '24564814', 'We measure the simultaneous dynamics of duplicate orthologous gene loss in rosids, in asterids, and in monocots, as influenced by biological functional class. This pan-angiosperm view confirms common tendencies and consistency through time for both ancient and more recent whole genome polyploidization events.'),
(96021, 2014, 'bmc', 'Statistical tests to identify appropriate types of nucleotide sequence recoding in molecular phylogenetics', 'Vera-Ruiz, Victor A|Lau, Kwok W|Robinson, John|Jermiin, Lars S', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China', 0, 'Animals|DNA, Mitochondrial|Likelihood Functions|Markov Chains|Nucleotides|Phylogeny|Primates|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1186/1471-2105-15-S2-S8', '24564837', 'Under a Markov model of evolution, recoding, or lumping, of the four nucleotides into fewer groups may permit analysis under simpler conditions but may unfortunately yield misleading results unless the evolutionary process of the recoded groups remains Markovian. If a Markov process is lumpable, then the evolutionary process of the recoded groups is Markovian.'),
(96022, 2013, 'bmc', 'The dynamics of alternative pathways to compensatory substitution', 'Nasrallah, Chris A', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China', 2, 'Evolution, Molecular|Genetics, Population|Models, Genetic|Mutation|Phylogeny|Probability|Selection, Genetic', 'Journal Article', '10.1186/1471-2105-14-S15-S2', '24564842', 'The role of epistatic interactions among loci is a central question in evolutionary biology and is increasingly relevant in the genomic age. While the population genetics of compensatory substitution have received considerable attention, most studies have focused on the case when natural selection is very strong against deleterious intermediates. In the biologically-plausible scenario of weak to moderate selection there exist two alternate pathways for compensatory substitution. In one pathway, a deleterious mutation becomes fixed prior to occurrence of the compensatory mutation. In the other, the two loci are simultaneously polymorphic. The rates of compensatory substitution along these two pathways and their relative probabilities are functions of the population size, selection strength, mutation rate, and recombination rate. In this paper these rates and path probabilities are derived analytically and verified using population genetic simulations. The expected time durations of these two paths are similar when selection is moderate, but not when selection is weak. The effect of recombination on the dynamics of the substitution process are explored using simulation. Using the derived rates, a phylogenetic substitution model of the compensatory evolution process is presented that could be used for inference of population genetic parameters from interspecific data. '),
(96023, 2014, 'bmc', 'Collective prediction of protein functions from protein-protein interaction networks', 'Wu, Qingyao|Ye, Yunming|Ng, Michael K|Ho, Shen-Shyang|Shi, Ruichao', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.', 'China|China|China|China|China', 14, 'Algorithms|Markov Chains|Protein Interaction Mapping|Proteins', 'Journal Article', '10.1186/1471-2105-15-S2-S9', '24564855', 'Automated assignment of functions to unknown proteins is one of the most important task in computational biology. The development of experimental methods for genome scale analysis of molecular interaction networks offers new ways to infer protein function from protein-protein interaction (PPI) network data. Existing techniques for collective classification (CC) usually increase accuracy for network data, wherein instances are interlinked with each other, using a large amount of labeled data for training. However, the labeled data are time-consuming and expensive to obtain. On the other hand, one can easily obtain large amount of unlabeled data. Thus, more sophisticated methods are needed to exploit the unlabeled data to increase prediction accuracy for protein function prediction.'),
(96024, 2014, 'bmc', 'Integrating water exclusion theory into xcexb2 contacts to predict binding free energy changes and binding hot spots', 'Liu, Qian|Hoi, Steven C H|Kwoh, Chee Keong|Wong, Limsoon|Li, Jinyan', 'Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China. jackyleehongjian@gmail.com.|Advanced Analytics Institute and Center for Health Technologies, Faculty of Engineering and IT, University of Technology, Sydney, Australia. jinyan.li@uts.edu.au.', 'China|China|China|China|Australia', 0, 'Alanine|Computational Biology|Models, Molecular|Mutation|Protein Binding|Proteins|Thermodynamics|Water', 'Journal Article', '10.1186/1471-2105-15-57', '24568581', 'Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss.'),
(96025, 2014, 'bmc', 'Combining techniques for screening and evaluating interaction terms on high-dimensional time-to-event data', 'Sariyar, Murat|Hoffmann, Isabell|Binder, Harald', 'Institute of Medical Biostatistics, Epidemiology and Informatics, Medical Center of the Johannes Gutenberg University, Mainz 55131, Germany. murat.sariyar@charite.de.|Institute of Medical Biostatistics, Epidemiology and Informatics, Medical Center of the Johannes Gutenberg University, Mainz 55131, Germany. murat.sariyar@charite.de.|Institute of Medical Biostatistics, Epidemiology and Informatics, Medical Center of the Johannes Gutenberg University, Mainz 55131, Germany. murat.sariyar@charite.de.', 'Germany|Germany|Germany', 0, 'Computational Biology|Databases, Factual|Decision Trees|High-Throughput Screening Assays|Humans|Models, Theoretical|Neoplasms|Risk|Survival Analysis', 'Journal Article', '10.1186/1471-2105-15-58', '24571520', 'Molecular data, e.g. arising from microarray technology, is often used for predicting survival probabilities of patients. For multivariate risk prediction models on such high-dimensional data, there are established techniques that combine parameter estimation and variable selection. One big challenge is to incorporate interactions into such prediction models. In this feasibility study, we present building blocks for evaluating and incorporating interactions terms in high-dimensional time-to-event settings, especially for settings in which it is computationally too expensive to check all possible interactions.'),
(96026, 2014, 'bmc', 'Large-scale biomedical concept recognition: an evaluation of current automatic annotators and their parameters', 'Funk, Christopher|Baumgartner, William|Garcia, Benjamin|Roeder, Christophe|Bada, Michael|Cohen, K Bretonnel|Hunter, Lawrence E|Verspoor, Karin', 'Computational Bioscience Program, U, of Colorado School of Medicine, Aurora, CO 80045, USA. christopher.funk@ucdenver.edu.|Computational Bioscience Program, U, of Colorado School of Medicine, Aurora, CO 80045, USA. christopher.funk@ucdenver.edu.|Computational Bioscience Program, U, of Colorado School of Medicine, Aurora, CO 80045, USA. christopher.funk@ucdenver.edu.|Computational Bioscience Program, U, of Colorado School of Medicine, Aurora, CO 80045, USA. christopher.funk@ucdenver.edu.|Computational Bioscience Program, U, of Colorado School of Medicine, Aurora, CO 80045, USA. christopher.funk@ucdenver.edu.|Computational Bioscience Program, U, of Colorado School of Medicine, Aurora, CO 80045, USA. christopher.funk@ucdenver.edu.|Computational Bioscience Program, U, of Colorado School of Medicine, Aurora, CO 80045, USA. christopher.funk@ucdenver.edu.|Computational Bioscience Program, U, of Colorado School of Medicine, Aurora, CO 80045, USA. christopher.funk@ucdenver.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States', 54, 'Biological Ontologies|Data Mining|Databases, Factual|Reproducibility of Results', 'Journal Article', '10.1186/1471-2105-15-59', '24571547', 'Ontological concepts are useful for many different biomedical tasks. Concepts are difficult to recognize in text due to a disconnect between what is captured in an ontology and how the concepts are expressed in text. There are many recognizers for specific ontologies, but a general approach for concept recognition is an open problem.'),
(96027, 2014, 'bmc', 'Analysing RNA-kinetics based on folding space abstraction', 'Huang, Jiabin|Voß, Björn', 'Computational Bioscience Program, U, of Colorado School of Medicine, Aurora, CO 80045, USA. christopher.funk@ucdenver.edu.|Genetics & Experimental Bioinformatics, Faculty of Biology, University of Freiburg, Schänzlestr, 1, 79104, Freiburg, Germany. bjoern.voss@biologie.uni-freiburg.de.', 'United States|Germany', 0, 'Algorithms|Base Sequence|Computational Biology|Kinetics|Molecular Sequence Data|Nucleic Acid Conformation|RNA|RNA Folding|Riboswitch|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-15-60', '24575751', 'RNA molecules, especially non-coding RNAs, play vital roles in the cell and their biological functions are mostly determined by structural properties. Often, these properties are related to dynamic changes in the structure, as in the case of riboswitches, and thus the analysis of RNA folding kinetics is crucial for their study. Exact approaches to kinetic folding are computationally expensive and, thus, limited to short sequences. In a previous study, we introduced a position-specific abstraction based on helices which we termed helix index shapes (hishapes) and a hishape-based algorithm for near-optimal folding pathway computation, called HiPath. The combination of these approaches provides an abstract view of the folding space that offers information about the global features.'),
(96028, 2014, 'bmc', 'CDSbank: taxonomy-aware extraction, selection, renaming and formatting of protein-coding DNA or amino acid sequences', 'Hazes, Bart', 'Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.', 'Canada', 2, 'Amino Acid Sequence|Base Sequence|DNA|Database Management Systems|Databases, Genetic|Databases, Nucleic Acid|Internet|Phylogeny|Proteins|Sequence Analysis, DNA|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-15-61', '24580755', 'Protein-coding DNA sequences and their corresponding amino acid sequences are routinely used to study relationships between sequence, structure, function, and evolution. The rapidly growing size of sequence databases increases the power of such comparative analyses but it makes it more challenging to prepare high quality sequence data sets with control over redundancy, quality, completeness, formatting, and labeling. Software tools for some individual steps in this process exist but manual intervention remains a common and time consuming necessity.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96029, 2014, 'bmc', 'Stability SCAD: a powerful approach to detect interactions in large-scale genomic study', 'Gou, Jianwei|Zhao, Yang|Wei, Yongyue|Wu, Chen|Zhang, Ruyang|Qiu, Yongyong|Zeng, Ping|Tan, Wen|Yu, Dianke|Wu, Tangchun|Hu, Zhibin|Lin, Dongxin|Shen, Hongbing|Chen, Feng', 'Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.|Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.|Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.|Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.|Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.|Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.|Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.|Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.|Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.|Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.|Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.|Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.|Department of Medical Microbiology & Immunology, 6-020 Katz Group Centre, University of Alberta, Edmonton, Alberta T6G 2E1, Canada. bart.hazes@ualberta.ca.|Department of Epidemiology and Biostatistics and Ministry of Education (MOE) Key Lab for Modern Toxicology, School of Public Health, Nanjing Medical University, Nanjing, China. fengchen@njmu.edu.cn.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|China', 2, 'Algorithms|Genome-Wide Association Study|Genomics|Humans|Logistic Models|Lung Neoplasms|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-15-62', '24580776', 'Evidence suggests that common complex diseases may be partially due to SNP-SNP interactions, but such detection is yet to be fully established in a high-dimensional small-sample (small-n-large-p) study. A number of penalized regression techniques are gaining popularity within the statistical community, and are now being applied to detect interactions. These techniques tend to be over-fitting, and are prone to false positives. The recently developed stability least absolute shrinkage and selection operator (SLASSO) has been used to control family-wise error rate, but often at the expense of power (and thus false negative results).'),
(96030, 2014, 'bmc', 'Identification of pathogen genomic variants through an integrated pipeline', 'Manary, Micah J|Singhakul, Suriya S|Flannery, Erika L|Bopp, Selina Er|Corey, Victoria C|Bright, Andrew Taylor|McNamara, Case W|Walker, John R|Winzeler, Elizabeth A', 'Department of Pediatrics, University of California, San Diego, School of Medicine, 9500 Gilman Drive 0741, La Jolla, California 92093, USA. mmanary@ucsd.edu.|Department of Pediatrics, University of California, San Diego, School of Medicine, 9500 Gilman Drive 0741, La Jolla, California 92093, USA. mmanary@ucsd.edu.|Department of Pediatrics, University of California, San Diego, School of Medicine, 9500 Gilman Drive 0741, La Jolla, California 92093, USA. mmanary@ucsd.edu.|Department of Pediatrics, University of California, San Diego, School of Medicine, 9500 Gilman Drive 0741, La Jolla, California 92093, USA. mmanary@ucsd.edu.|Department of Pediatrics, University of California, San Diego, School of Medicine, 9500 Gilman Drive 0741, La Jolla, California 92093, USA. mmanary@ucsd.edu.|Department of Pediatrics, University of California, San Diego, School of Medicine, 9500 Gilman Drive 0741, La Jolla, California 92093, USA. mmanary@ucsd.edu.|Department of Pediatrics, University of California, San Diego, School of Medicine, 9500 Gilman Drive 0741, La Jolla, California 92093, USA. mmanary@ucsd.edu.|Department of Pediatrics, University of California, San Diego, School of Medicine, 9500 Gilman Drive 0741, La Jolla, California 92093, USA. mmanary@ucsd.edu.|Department of Pediatrics, University of California, San Diego, School of Medicine, 9500 Gilman Drive 0741, La Jolla, California 92093, USA. mmanary@ucsd.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Antimalarials|DNA Copy Number Variations|DNA, Protozoan|Drug Resistance|Genome, Protozoan|Genomics|Plasmodium falciparum|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-15-63', '24589256', 'Whole-genome sequencing represents a powerful experimental tool for pathogen research. We present methods for the analysis of small eukaryotic genomes, including a streamlined system (called Platypus) for finding single nucleotide and copy number variants as well as recombination events.'),
(96031, 2014, 'bmc', 'Knowledge-based extraction of adverse drug events from biomedical text', 'Kang, Ning|Singh, Bharat|Bui, Chinh|Afzal, Zubair|van Mulligen, Erik M|Kors, Jan A', 'Department of Medical Informatics, Erasmus University Medical Center, P,O, Box 2040, 3000, CA, Rotterdam, The Netherlands. n.kang@erasmusmc.nl.|Department of Medical Informatics, Erasmus University Medical Center, P,O, Box 2040, 3000, CA, Rotterdam, The Netherlands. n.kang@erasmusmc.nl.|Department of Medical Informatics, Erasmus University Medical Center, P,O, Box 2040, 3000, CA, Rotterdam, The Netherlands. n.kang@erasmusmc.nl.|Department of Medical Informatics, Erasmus University Medical Center, P,O, Box 2040, 3000, CA, Rotterdam, The Netherlands. n.kang@erasmusmc.nl.|Department of Medical Informatics, Erasmus University Medical Center, P,O, Box 2040, 3000, CA, Rotterdam, The Netherlands. n.kang@erasmusmc.nl.|Department of Medical Informatics, Erasmus University Medical Center, P,O, Box 2040, 3000, CA, Rotterdam, The Netherlands. n.kang@erasmusmc.nl.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 41, 'Artificial Intelligence|Data Mining|Drug-Related Side Effects and Adverse Reactions|Humans|Knowledge Bases|Unified Medical Language System', 'Journal Article', '10.1186/1471-2105-15-64', '24593054', 'Many biomedical relation extraction systems are machine-learning based and have to be trained on large annotated corpora that are expensive and cumbersome to construct. We developed a knowledge-based relation extraction system that requires minimal training data, and applied the system for the extraction of adverse drug events from biomedical text. The system consists of a concept recognition module that identifies drugs and adverse effects in sentences, and a knowledge-base module that establishes whether a relation exists between the recognized concepts. The knowledge base was filled with information from the Unified Medical Language System. The performance of the system was evaluated on the ADE corpus, consisting of 1644 abstracts with manually annotated adverse drug events. Fifty abstracts were used for training, the remaining abstracts were used for testing.'),
(96032, 2014, 'bmc', 'eCAMBer: efficient support for large-scale comparative analysis of multiple bacterial strains', 'Wozniak, Michal|Wong, Limsoon|Tiuryn, Jerzy', 'Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland. m.wozniak@mimuw.edu.pl.|Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland. m.wozniak@mimuw.edu.pl.|Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland. m.wozniak@mimuw.edu.pl.', 'Poland|Poland|Poland', 0, 'Bacteria|Genome, Bacterial|Molecular Sequence Annotation|Multigene Family|Software', 'Journal Article', '10.1186/1471-2105-15-65', '24597904', 'Inconsistencies are often observed in the genome annotations of bacterial strains. Moreover, these inconsistencies are often not reflected by sequence discrepancies, but are caused by wrongly annotated gene starts as well as mis-identified gene presence. Thus, tools are needed for improving annotation consistency and accuracy among sets of bacterial strain genomes.'),
(96033, 2014, 'bmc', 'Information compression exploits patterns of genome composition to discriminate populations and highlight regions of evolutionary interest', 'Hudson, Nicholas J|Porto-Neto, Laercio R|Kijas, James|McWilliam, Sean|Taft, Ryan J|Reverter, Antonio', 'Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland. m.wozniak@mimuw.edu.pl.|Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland. m.wozniak@mimuw.edu.pl.|Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland. m.wozniak@mimuw.edu.pl.|Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland. m.wozniak@mimuw.edu.pl.|Computational and Systems Biology, CSIRO Animal, Food and Health Sciences, St, Lucia, Brisbane, QLD 4067, Australia. r.taft@imb.uq.edu.au.|Computational and Systems Biology, CSIRO Animal, Food and Health Sciences, St, Lucia, Brisbane, QLD 4067, Australia. r.taft@imb.uq.edu.au.', 'Poland|Poland|Poland|Poland|Australia|Australia', 0, 'Animals|Cattle|Cluster Analysis|Data Compression|Databases, Genetic|Dogs|Evolution, Molecular|Genome|Genomics|Humans|Mice|Phylogeography|Polymorphism, Single Nucleotide|Sheep', 'Journal Article', '10.1186/1471-2105-15-66', '24606587', 'Genomic information allows population relatedness to be inferred and selected genes to be identified. Single nucleotide polymorphism microarray (SNP-chip) data, a proxy for genome composition, contains patterns in allele order and proportion. These patterns can be quantified by compression efficiency (CE). In principle, the composition of an entire genome can be represented by a CE number quantifying allele representation and order.'),
(96034, 2014, 'bmc', 'Drug2Gene: an exhaustive resource to explore effectively the drug-target relation network', 'Roider, Helge G|Pavlova, Nadia|Kirov, Ivaylo|Slavov, Stoyan|Slavov, Todor|Uzunov, Zlatyo|Weiss, Bertram', 'Computational and Systems Biology, CSIRO Animal, Food and Health Sciences, St, Lucia, Brisbane, QLD 4067, Australia. r.taft@imb.uq.edu.au.|Computational and Systems Biology, CSIRO Animal, Food and Health Sciences, St, Lucia, Brisbane, QLD 4067, Australia. r.taft@imb.uq.edu.au.|Computational and Systems Biology, CSIRO Animal, Food and Health Sciences, St, Lucia, Brisbane, QLD 4067, Australia. r.taft@imb.uq.edu.au.|Computational and Systems Biology, CSIRO Animal, Food and Health Sciences, St, Lucia, Brisbane, QLD 4067, Australia. r.taft@imb.uq.edu.au.|Computational and Systems Biology, CSIRO Animal, Food and Health Sciences, St, Lucia, Brisbane, QLD 4067, Australia. r.taft@imb.uq.edu.au.|Computational and Systems Biology, CSIRO Animal, Food and Health Sciences, St, Lucia, Brisbane, QLD 4067, Australia. r.taft@imb.uq.edu.au.|Bayer Pharma AG, Müllerstr 178, 13342 Berlin, Germany. bertram.weiss@bayer.com.', 'Australia|Australia|Australia|Australia|Australia|Australia|Germany', 0, 'Algorithms|Data Mining|Databases, Genetic|Drug Discovery|Humans|Proteins|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-15-68', '24618344', 'Information about drug-target relations is at the heart of drug discovery. There are now dozens of databases providing drug-target interaction data with varying scope, and focus. Therefore, and due to the large chemical space, the overlap of the different data sets is surprisingly small. As searching through these sources manually is cumbersome, time-consuming and error-prone, integrating all the data is highly desirable. Despite a few attempts, integration has been hampered by the diversity of descriptions of compounds, and by the fact that the reported activity values, coming from different data sets, are not always directly comparable due to usage of different metrics or data formats.'),
(96035, 2014, 'bmc', 'MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data', 'Gan, Zhuohui|Wang, Jianwu|Salomonis, Nathan|Stowe, Jennifer C|Haddad, Gabriel G|McCulloch, Andrew D|Altintas, Ilkay|Zambon, Alexander C', 'Bayer Pharma AG, Müllerstr 178, 13342 Berlin, Germany. bertram.weiss@bayer.com.|Bayer Pharma AG, Müllerstr 178, 13342 Berlin, Germany. bertram.weiss@bayer.com.|Bayer Pharma AG, Müllerstr 178, 13342 Berlin, Germany. bertram.weiss@bayer.com.|Bayer Pharma AG, Müllerstr 178, 13342 Berlin, Germany. bertram.weiss@bayer.com.|Bayer Pharma AG, Müllerstr 178, 13342 Berlin, Germany. bertram.weiss@bayer.com.|Bayer Pharma AG, Müllerstr 178, 13342 Berlin, Germany. bertram.weiss@bayer.com.|Bayer Pharma AG, Müllerstr 178, 13342 Berlin, Germany. bertram.weiss@bayer.com.|Department of Pharmacology, University of California, San Diego, La Jolla, CA, USA. azambon@ucsd.edu.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|United States', 0, 'Animals|Computational Biology|Databases, Genetic|Drosophila|Meta-Analysis as Topic|Mice|Oligonucleotide Array Sequence Analysis|Quality Control|Software', 'Journal Article', '10.1186/1471-2105-15-69', '24621103', 'Mandatory deposit of raw microarray data files for public access, prior to study publication, provides significant opportunities to conduct new bioinformatics analyses within and across multiple datasets. Analysis of raw microarray data files (e.g. Affymetrix CEL files) can be time consuming, complex, and requires fundamental computational and bioinformatics skills. The development of analytical workflows to automate these tasks simplifies the processing of, improves the efficiency of, and serves to standardize multiple and sequential analyses. Once installed, workflows facilitate the tedious steps required to run rapid intra- and inter-dataset comparisons.'),
(96036, 2013, 'bmc', 'Proceedings of the 2013 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference, April 5-6, 2013, Columbia, Missouri', '-', '-', '-', 11, 'Animals|Computational Biology|Humans', 'Congress', '10.1186/1471-2105-15-69', '24624436', '-'),
(96037, 2013, 'bmc', 'Proceedings of the 12th Annual UT-ORNL-KBRIN Bioinformatics Summit 2013', 'Rouchka, Eric C|Flight, Robert M', 'Department of Pharmacology, University of California, San Diego, La Jolla, CA, USA. azambon@ucsd.edu.|Department of Pharmacology, University of California, San Diego, La Jolla, CA, USA. azambon@ucsd.edu.', 'United States|United States', 0, 'Child|Child Development|Cognition|Computational Biology|Genomics|Humans|Sequence Analysis|Software|Systems Biology|Translational Medical Research', 'Congress', '10.1186/1471-2105-15-69', '24625056', '-'),
(96038, 2014, 'bmc', 'Feature weight estimation for gene selection: a local hyperlinear learning approach', 'Cai, Hongmin|Ruan, Peiying|Ng, Michael|Akutsu, Tatsuya', 'School of Computer Science and Engineering, South China University of Technology, Guangdong, China. hmcai@scut.edu.cn.|School of Computer Science and Engineering, South China University of Technology, Guangdong, China. hmcai@scut.edu.cn.|School of Computer Science and Engineering, South China University of Technology, Guangdong, China. hmcai@scut.edu.cn.|School of Computer Science and Engineering, South China University of Technology, Guangdong, China. hmcai@scut.edu.cn.', 'China|China|China|China', 0, 'Algorithms|Bayes Theorem|Cluster Analysis|Computational Biology|Databases, Genetic|Discriminant Analysis|Gene Expression Profiling|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-15-70', '24625071', 'Modeling high-dimensional data involving thousands of variables is particularly important for gene expression profiling experiments, nevertheless,it remains a challenging task. One of the challenges is to implement an effective method for selecting a small set of relevant genes, buried in high-dimensional irrelevant noises. RELIEF is a popular and widely used approach for feature selection owing to its low computational cost and high accuracy. However, RELIEF based methods suffer from instability, especially in the presence of noisy and/or high-dimensional outliers.'),
(96039, 2014, 'bmc', 'Transposon Insertion Finder (TIF): a novel program for detection of de novo transpositions of transposable elements', 'Nakagome, Mariko|Solovieva, Elena|Takahashi, Akira|Yasue, Hiroshi|Hirochika, Hirohiko|Miyao, Akio', 'School of Computer Science and Engineering, South China University of Technology, Guangdong, China. hmcai@scut.edu.cn.|School of Computer Science and Engineering, South China University of Technology, Guangdong, China. hmcai@scut.edu.cn.|School of Computer Science and Engineering, South China University of Technology, Guangdong, China. hmcai@scut.edu.cn.|School of Computer Science and Engineering, South China University of Technology, Guangdong, China. hmcai@scut.edu.cn.|School of Computer Science and Engineering, South China University of Technology, Guangdong, China. hmcai@scut.edu.cn.|Agrogenomics Research Center, National Institute of Agrobiological Sciences, 2-1-2, Kannondai, Tsukuba, Ibaraki 305-8602, Japan. miyao@affrc.go.jp.', 'China|China|China|China|China|Japan', 0, 'Algorithms|Animals|DNA Transposable Elements|Drosophila melanogaster|Genomics|High-Throughput Nucleotide Sequencing|Oryza|Polymerase Chain Reaction|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-15-71', '24629057', 'Transposition event detection of transposable element (TE) in the genome using short reads from the next-generation sequence (NGS) was difficult, because the nucleotide sequence of TE itself is repetitive, making it difficult to identify locations of its insertions by alignment programs for NGS. We have developed a program with a new algorithm to detect the transpositions from NGS data.'),
(96040, 2014, 'bmc', 'Natural polymorphisms and unusual mutations in HIV-1 protease with potential antiretroviral resistance: a bioinformatic analysis', 'Mata-Munguía, Carlos|Escoto-Delgadillo, Martha|Torres-Mendoza, Blanca|Flores-Soto, Mario|Vázquez-Torres, Mildred|Gálvez-Gastelum, Francisco|Viniegra-Osorio, Arturo|Castillero-Manzano, Marcelo|Vázquez-Valls, Eduardo', 'Agrogenomics Research Center, National Institute of Agrobiological Sciences, 2-1-2, Kannondai, Tsukuba, Ibaraki 305-8602, Japan. miyao@affrc.go.jp.|Agrogenomics Research Center, National Institute of Agrobiological Sciences, 2-1-2, Kannondai, Tsukuba, Ibaraki 305-8602, Japan. miyao@affrc.go.jp.|Agrogenomics Research Center, National Institute of Agrobiological Sciences, 2-1-2, Kannondai, Tsukuba, Ibaraki 305-8602, Japan. miyao@affrc.go.jp.|Agrogenomics Research Center, National Institute of Agrobiological Sciences, 2-1-2, Kannondai, Tsukuba, Ibaraki 305-8602, Japan. miyao@affrc.go.jp.|Agrogenomics Research Center, National Institute of Agrobiological Sciences, 2-1-2, Kannondai, Tsukuba, Ibaraki 305-8602, Japan. miyao@affrc.go.jp.|Agrogenomics Research Center, National Institute of Agrobiological Sciences, 2-1-2, Kannondai, Tsukuba, Ibaraki 305-8602, Japan. miyao@affrc.go.jp.|Agrogenomics Research Center, National Institute of Agrobiological Sciences, 2-1-2, Kannondai, Tsukuba, Ibaraki 305-8602, Japan. miyao@affrc.go.jp.|Agrogenomics Research Center, National Institute of Agrobiological Sciences, 2-1-2, Kannondai, Tsukuba, Ibaraki 305-8602, Japan. miyao@affrc.go.jp.|Laboratorio de Inmunodeficiencias y Retrovirus Humanos, Centro de Investigación Biomédica de Occidente, CMNO, IMSS, Guadalajara 44340, México. eduardo.vazquez@imss.gob.mx.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|-', 0, 'Atazanavir Sulfate|Base Sequence|Darunavir|Drug Resistance, Viral|Female|HIV Infections|HIV Protease|HIV Protease Inhibitors|HIV-1|Humans|Male|Molecular Docking Simulation|Molecular Sequence Data|Mutation|Oligopeptides|Phenotype|Polymorphism, Genetic|Pyridines|Pyrones|Sulfonamides', 'Journal Article', '10.1186/1471-2105-15-72', '24629078', 'The correlations of genotypic and phenotypic tests with treatment, clinical history and the significance of mutations in viruses of HIV-infected patients are used to establish resistance mutations to protease inhibitors (PIs). Emerging mutations in human immunodeficiency virus type 1 (HIV-1) protease confer resistance to PIs by inducing structural changes at the ligand interaction site. The aim of this study was to establish an in silico structural relationship between natural HIV-1 polymorphisms and unusual HIV-1 mutations that confer resistance to PIs.'),
(96041, 2014, 'bmc', 'mrSNP: software to detect SNP effects on microRNA binding', 'Deveci, Mehmet|Catalyürek, Umit V|Toland, Amanda Ewart', 'Biomedical Informatics, Computer Science and Engineering, The Ohio State University, Columbus, Ohio, USA. mdeveci@bmi.osu.edu.|Biomedical Informatics, Computer Science and Engineering, The Ohio State University, Columbus, Ohio, USA. mdeveci@bmi.osu.edu.|Biomedical Informatics, Computer Science and Engineering, The Ohio State University, Columbus, Ohio, USA. mdeveci@bmi.osu.edu.', 'United States|United States|United States', 0, '3 Untranslated Regions|Algorithms|Binding Sites|Humans|MicroRNAs|Polymorphism, Single Nucleotide|RNA, Messenger|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-15-73', '24629096', 'MicroRNAs (miRNAs) are short (19-23 nucleotides) non-coding RNAs that bind to sites in the 3untranslated regions (3UTR) of a targeted messenger RNA (mRNA). Binding leads to degradation of the transcript or blocked translation resulting in decreased expression of the targeted gene. Single nucleotide polymorphisms (SNPs) have been found in 3UTRs that disrupt normal miRNA binding or introduce new binding sites and some of these have been associated with disease pathogenesis. This raises the importance of detecting miRNA targets and predicting the possible effects of SNPs on binding sites. In the last decade a number of studies have been conducted to predict the location of miRNA binding sites. However, there have been fewer algorithms published to analyze the effects of SNPs on miRNA binding. Moreover, the existing software has some shortcomings including the requirement for significant manual labor when working with huge lists of SNPs and that algorithms work only for SNPs present in databases such as dbSNP. These limitations become problematic as next-generation sequencing is leading to large numbers of novel variants in 3UTRs.'),
(96042, 2014, 'bmc', 'BCRgt: a Bayesian cluster regression-based genotyping algorithm for the samples with copy number alterations', 'Yang, Shengping|Cui, Xiangqin|Fang, Zhide', 'Biomedical Informatics, Computer Science and Engineering, The Ohio State University, Columbus, Ohio, USA. mdeveci@bmi.osu.edu.|Biomedical Informatics, Computer Science and Engineering, The Ohio State University, Columbus, Ohio, USA. mdeveci@bmi.osu.edu.|Biostatistics Program, School of Public Health, LSU Health Sciences Center, 2020 Gravier Street, New Orleans, LA 70115, USA. zfang@lsuhsc.edu.', 'United States|United States|United States', 0, 'Algorithms|Bayes Theorem|Cluster Analysis|DNA Copy Number Variations|Genome-Wide Association Study|Genotype|Genotyping Techniques|Humans|Neoplasms|Polymorphism, Single Nucleotide|Regression Analysis', 'Journal Article', '10.1186/1471-2105-15-74', '24629125', 'Accurate genotype calling is a pre-requisite of a successful Genome-Wide Association Study (GWAS). Although most genotyping algorithms can achieve an accuracy rate greater than 99% for genotyping DNA samples without copy number alterations (CNAs), almost all of these algorithms are not designed for genotyping tumor samples that are known to have large regions of CNAs.'),
(96043, 2014, 'bmc', 'Structure and computational analysis of a novel protein with metallopeptidase-like and circularly permuted winged-helix-turn-helix domains reveals a possible role in modified polysaccharide biosynthesis', 'Das, Debanu|Murzin, Alexey G|Rawlings, Neil D|Finn, Robert D|Coggill, Penelope|Bateman, Alex|Godzik, Adam|Aravind, L', 'Joint Center for Structural Genomics, La Jolla, CA, USA. debanu@slac.stanford.edu.|Joint Center for Structural Genomics, La Jolla, CA, USA. debanu@slac.stanford.edu.|Joint Center for Structural Genomics, La Jolla, CA, USA. debanu@slac.stanford.edu.|Joint Center for Structural Genomics, La Jolla, CA, USA. debanu@slac.stanford.edu.|Joint Center for Structural Genomics, La Jolla, CA, USA. debanu@slac.stanford.edu.|Joint Center for Structural Genomics, La Jolla, CA, USA. debanu@slac.stanford.edu.|Joint Center for Structural Genomics, La Jolla, CA, USA. debanu@slac.stanford.edu.|Joint Center for Structural Genomics, La Jolla, CA, USA. debanu@slac.stanford.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States', 1, 'Bacterial Proteins|Clostridium acetobutylicum|Crystallography, X-Ray|Metalloproteases|Models, Molecular|Protein Structure, Tertiary', 'Journal Article', '10.1186/1471-2105-15-75', '24646163', 'CA_C2195 from Clostridium acetobutylicum is a protein of unknown function. Sequence analysis predicted that part of the protein contained a metallopeptidase-related domain. There are over 200 homologs of similar size in large sequence databases such as UniProt, with pairwise sequence identities in the range of ~40-60%. CA_C2195 was chosen for crystal structure determination for structure-based function annotation of novel protein sequence space.'),
(96044, 2014, 'bmc', 'Metavir 2: new tools for viral metagenome comparison and assembled virome analysis', 'Roux, Simon|Tournayre, Jeremy|Mahul, Antoine|Debroas, Didier|Enault, François', 'Joint Center for Structural Genomics, La Jolla, CA, USA. debanu@slac.stanford.edu.|Joint Center for Structural Genomics, La Jolla, CA, USA. debanu@slac.stanford.edu.|Joint Center for Structural Genomics, La Jolla, CA, USA. debanu@slac.stanford.edu.|Joint Center for Structural Genomics, La Jolla, CA, USA. debanu@slac.stanford.edu.|Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, Clermont-Ferrand, France. francois.enault@univ-bpclermont.fr.', 'United States|United States|United States|United States|France', 0, 'Genome, Viral|Humans|Intestines|Metagenome|Metagenomics|Phylogeny|Software', 'Comparative Study', '10.1186/1471-2105-15-76', '24646187', 'Metagenomics, based on culture-independent sequencing, is a well-fitted approach to provide insights into the composition, structure and dynamics of environmental viral communities. Following recent advances in sequencing technologies, new challenges arise for existing bioinformatic tools dedicated to viral metagenome (i.e. virome) analysis as (i) the number of viromes is rapidly growing and (ii) large genomic fragments can now be obtained by assembling the huge amount of sequence data generated for each metagenome.'),
(96045, 2014, 'bmc', 'Predicting HIV-1 broadly neutralizing antibody epitope networks using neutralization titers and a novel computational method', 'Evans, Mark C|Phung, Pham|Paquet, Agnes C|Parikh, Anvi|Petropoulos, Christos J|Wrin, Terri|Haddad, Mojgan', 'Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, Clermont-Ferrand, France. francois.enault@univ-bpclermont.fr.|Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, Clermont-Ferrand, France. francois.enault@univ-bpclermont.fr.|Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, Clermont-Ferrand, France. francois.enault@univ-bpclermont.fr.|Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, Clermont-Ferrand, France. francois.enault@univ-bpclermont.fr.|Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, Clermont-Ferrand, France. francois.enault@univ-bpclermont.fr.|Laboratoire Microorganismes: Génome et Environnement, Clermont Université, Université Blaise Pascal, Clermont-Ferrand, France. francois.enault@univ-bpclermont.fr.|Monogram Biosciences Inc,, 345 Oyster Point Blvd,, South San Francisco, CA 94080, USA. mojganhd@yahoo.com.', 'France|France|France|France|France|France|United States', 0, 'Antibodies, Monoclonal|Antibodies, Neutralizing|Binding Sites, Antibody|Computational Biology|Epitopes|HIV Antibodies|HIV Envelope Protein gp120|HIV-1|Humans|Neutralization Tests', 'Journal Article', '10.1186/1471-2105-15-77', '24646213', 'Recent efforts in HIV-1 vaccine design have focused on immunogens that evoke potent neutralizing antibody responses to a broad spectrum of viruses circulating worldwide. However, the development of effective vaccines will depend on the identification and characterization of the neutralizing antibodies and their epitopes. We developed bioinformatics methods to predict epitope networks and antigenic determinants using structural information, as well as corresponding genotypes and phenotypes generated by a highly sensitive and reproducible neutralization assay.282 clonal envelope sequences from a multiclade panel of HIV-1 viruses were tested in viral neutralization assays with an array of broadly neutralizing monoclonal antibodies (mAbs: b12, PG9,16, PGT121 - 128, PGT130 - 131, PGT135 - 137, PGT141 - 145, and PGV04). We correlated IC50 titers with the envelope sequences, and used this information to predict antibody epitope networks. Structural patches were defined as amino acid groups based on solvent-accessibility, radius, atomic depth, and interaction networks within 3D envelope models. We applied a boosted algorithm consisting of multiple machine-learning and statistical models to evaluate these patches as possible antibody epitope regions, evidenced by strong correlations with the neutralization response for each antibody.'),
(96046, 2014, 'bmc', 'ShatterProof: operational detection and quantification of chromothripsis', 'Govind, Shaylan K|Zia, Amin|Hennings-Yeomans, Pablo H|Watson, John D|Fraser, Michael|Anghel, Catalina|Wyatt, Alexander W|van der Kwast, Theodorus|Collins, Colin C|McPherson, John D|Bristow, Robert G|Boutros, Paul C', 'Monogram Biosciences Inc,, 345 Oyster Point Blvd,, South San Francisco, CA 94080, USA. mojganhd@yahoo.com.|Monogram Biosciences Inc,, 345 Oyster Point Blvd,, South San Francisco, CA 94080, USA. mojganhd@yahoo.com.|Monogram Biosciences Inc,, 345 Oyster Point Blvd,, South San Francisco, CA 94080, USA. mojganhd@yahoo.com.|Monogram Biosciences Inc,, 345 Oyster Point Blvd,, South San Francisco, CA 94080, USA. mojganhd@yahoo.com.|Monogram Biosciences Inc,, 345 Oyster Point Blvd,, South San Francisco, CA 94080, USA. mojganhd@yahoo.com.|Monogram Biosciences Inc,, 345 Oyster Point Blvd,, South San Francisco, CA 94080, USA. mojganhd@yahoo.com.|Monogram Biosciences Inc,, 345 Oyster Point Blvd,, South San Francisco, CA 94080, USA. mojganhd@yahoo.com.|Monogram Biosciences Inc,, 345 Oyster Point Blvd,, South San Francisco, CA 94080, USA. mojganhd@yahoo.com.|Monogram Biosciences Inc,, 345 Oyster Point Blvd,, South San Francisco, CA 94080, USA. mojganhd@yahoo.com.|Monogram Biosciences Inc,, 345 Oyster Point Blvd,, South San Francisco, CA 94080, USA. mojganhd@yahoo.com.|Monogram Biosciences Inc,, 345 Oyster Point Blvd,, South San Francisco, CA 94080, USA. mojganhd@yahoo.com.|Ontario Institute for Cancer Research, M5G 0A3, Toronto, Canada. Paul.Boutros@oicr.on.ca.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|Canada', 0, 'Algorithms|Chromosome Aberrations|DNA Copy Number Variations|Gene Rearrangement|Genomics|High-Throughput Nucleotide Sequencing|Humans|Male|Neoplasms|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-15-78', '24646301', 'Chromothripsis, a newly discovered type of complex genomic rearrangement, has been implicated in the evolution of several types of cancers. To date, it has been described in bone cancer, SHH-medulloblastoma and acute myeloid leukemia, amongst others, however there are still no formal or automated methods for detecting or annotating it in high throughput sequencing data. As such, findings of chromothripsis are difficult to compare and many cases likely escape detection altogether.'),
(96047, 2014, 'bmc', 'The characteristic direction: a geometrical approach to identify differentially expressed genes', 'Clark, Neil R|Hu, Kevin S|Feldmann, Axel S|Kou, Yan|Chen, Edward Y|Duan, Qiaonan|Maayan, Avi', 'Ontario Institute for Cancer Research, M5G 0A3, Toronto, Canada. Paul.Boutros@oicr.on.ca.|Ontario Institute for Cancer Research, M5G 0A3, Toronto, Canada. Paul.Boutros@oicr.on.ca.|Ontario Institute for Cancer Research, M5G 0A3, Toronto, Canada. Paul.Boutros@oicr.on.ca.|Ontario Institute for Cancer Research, M5G 0A3, Toronto, Canada. Paul.Boutros@oicr.on.ca.|Ontario Institute for Cancer Research, M5G 0A3, Toronto, Canada. Paul.Boutros@oicr.on.ca.|Ontario Institute for Cancer Research, M5G 0A3, Toronto, Canada. Paul.Boutros@oicr.on.ca.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Icahn School of Medicine at Mount Sinai School, New York, NY 10029, USA. avi.maayan@mssm.edu.', 'Canada|Canada|Canada|Canada|Canada|Canada|United States', 0, 'Computational Biology|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|Proteins|Software', 'Journal Article', '10.1186/1471-2105-15-79', '24650281', 'Identifying differentially expressed genes (DEG) is a fundamental step in studies that perform genome wide expression profiling. Typically, DEG are identified by univariate approaches such as Significance Analysis of Microarrays (SAM) or Linear Models for Microarray Data (LIMMA) for processing cDNA microarrays, and differential gene expression analysis based on the negative binomial distribution (DESeq) or Empirical analysis of Digital Gene Expression data in R (edgeR) for RNA-seq profiling.'),
(96048, 2014, 'bmc', 'The empirical codon mutation matrix as a communication channel', 'Nigatu, Dawit|Mahmood, Attiya|Henkel, Werner', 'Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Icahn School of Medicine at Mount Sinai School, New York, NY 10029, USA. avi.maayan@mssm.edu.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Icahn School of Medicine at Mount Sinai School, New York, NY 10029, USA. avi.maayan@mssm.edu.|School of Engineering and Science, Jacobs University Bremen, Campus Ring 1, D-28759 Bremen, Germany. w.henkel@jacobs-university.de.', 'United States|United States|Germany', 3, 'Amino Acids|Animals|Base Sequence|Codon|Humans|Models, Genetic|Mutation|Probability|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-15-80', '24655606', 'A number of evolutionary models have been widely used for sequence alignment, phylogenetic tree reconstruction, and database searches. These models focus on how sets of independent substitutions between amino acids or codons derive one protein sequence from its ancestral sequence during evolution. In this paper, we regard the Empirical Codon Mutation (ECM) Matrix as a communication channel and compute the corresponding channel capacity.'),
(96049, 2014, 'bmc', 'spliceR: an R package for classification of alternative splicing and prediction of coding potential from RNA-seq data', 'Vitting-Seerup, Kristoffer|Porse, Bo Torben|Sandelin, Albin|Waage, Johannes', 'School of Engineering and Science, Jacobs University Bremen, Campus Ring 1, D-28759 Bremen, Germany. w.henkel@jacobs-university.de.|School of Engineering and Science, Jacobs University Bremen, Campus Ring 1, D-28759 Bremen, Germany. w.henkel@jacobs-university.de.|Department of Biology, The Bioinformatics Centre, University of Copenhagen, Ole Maaloes Vej 5, Copenhagen, DK2200, Denmark. albin@binf.ku.dk.|Department of Biology, The Bioinformatics Centre, University of Copenhagen, Ole Maaloes Vej 5, Copenhagen, DK2200, Denmark. albin@binf.ku.dk.', 'Germany|Germany|Denmark|Denmark', 46, 'Alternative Splicing|Base Sequence|Exons|HCT116 Cells|Humans|Introns|Protein Isoforms|RNA, Messenger|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-15-81', '24655717', 'RNA-seq data is currently underutilized, in part because it is difficult to predict the functional impact of alternate transcription events. Recent software improvements in full-length transcript deconvolution prompted us to develop spliceR, an R package for classification of alternative splicing and prediction of coding potential.'),
(96050, 2014, 'bmc', 'Transient protein-protein interface prediction: datasets, features, algorithms, and the RAD-T predictor', 'Bendell, Calem J|Liu, Shalon|Aumentado-Armstrong, Tristan|Istrate, Bogdan|Cernek, Paul T|Khan, Samuel|Picioreanu, Sergiu|Zhao, Michael|Murgita, Robert A', 'Department of Biology, The Bioinformatics Centre, University of Copenhagen, Ole Maaloes Vej 5, Copenhagen, DK2200, Denmark. albin@binf.ku.dk.|Department of Biology, The Bioinformatics Centre, University of Copenhagen, Ole Maaloes Vej 5, Copenhagen, DK2200, Denmark. albin@binf.ku.dk.|Department of Biology, The Bioinformatics Centre, University of Copenhagen, Ole Maaloes Vej 5, Copenhagen, DK2200, Denmark. albin@binf.ku.dk.|Department of Biology, The Bioinformatics Centre, University of Copenhagen, Ole Maaloes Vej 5, Copenhagen, DK2200, Denmark. albin@binf.ku.dk.|Department of Biology, The Bioinformatics Centre, University of Copenhagen, Ole Maaloes Vej 5, Copenhagen, DK2200, Denmark. albin@binf.ku.dk.|Department of Biology, The Bioinformatics Centre, University of Copenhagen, Ole Maaloes Vej 5, Copenhagen, DK2200, Denmark. albin@binf.ku.dk.|Department of Biology, The Bioinformatics Centre, University of Copenhagen, Ole Maaloes Vej 5, Copenhagen, DK2200, Denmark. albin@binf.ku.dk.|Department of Biology, The Bioinformatics Centre, University of Copenhagen, Ole Maaloes Vej 5, Copenhagen, DK2200, Denmark. albin@binf.ku.dk.|Department of Microbiology and Immunology, McGill, Montreal, CA. robert.murgita@mcgill.ca.', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|-', 0, 'Algorithms|Artificial Intelligence|Binding Sites|Protein Interaction Domains and Motifs|Proteins', 'Journal Article', '10.1186/1471-2105-15-82', '24661439', 'Transient protein-protein interactions (PPIs), which underly most biological processes, are a prime target for therapeutic development. Immense progress has been made towards computational prediction of PPIs using methods such as protein docking and sequence analysis. However, docking generally requires high resolution structures of both of the binding partners and sequence analysis requires that a significant number of recurrent patterns exist for the identification of a potential binding site. Researchers have turned to machine learning to overcome some of the other methods restrictions by generalising interface sites with sets of descriptive features. Best practices for dataset generation, features, and learning algorithms have not yet been identified or agreed upon, and an analysis of the overall efficacy of machine learning based PPI predictors is due, in order to highlight potential areas for improvement.'),
(96051, 2014, 'bmc', 'Bioinformatics analysis of transcriptional regulation of circadian genes in rat liver', 'Nguyen, Tung T|Mattick, John S A|Yang, Qian|Orman, Mehmet A|Ierapetritou, Marianthi G|Berthiaume, Francois|Androulakis, Ioannis P', 'Department of Microbiology and Immunology, McGill, Montreal, CA. robert.murgita@mcgill.ca.|Department of Microbiology and Immunology, McGill, Montreal, CA. robert.murgita@mcgill.ca.|Department of Microbiology and Immunology, McGill, Montreal, CA. robert.murgita@mcgill.ca.|Department of Microbiology and Immunology, McGill, Montreal, CA. robert.murgita@mcgill.ca.|Department of Microbiology and Immunology, McGill, Montreal, CA. robert.murgita@mcgill.ca.|Department of Microbiology and Immunology, McGill, Montreal, CA. robert.murgita@mcgill.ca.|Chemical and Biochemical Engineering Department, Rutgers the State University of New Jersey, Piscataway, NJ 08854, USA. yannis@rci.rutgers.edu.', 'United States|United States|United States|United States|United States|United States|Jersey', 0, 'Animals|Binding Sites|Circadian Rhythm|Circadian Rhythm Signaling Peptides and Proteins|Computational Biology|Gene Expression Profiling|Gene Expression Regulation|Liver|Male|Oligonucleotide Array Sequence Analysis|Promoter Regions, Genetic|Rats|Rats, Sprague-Dawley|Transcription Factors', 'Journal Article', '10.1186/1471-2105-15-83', '24666587', 'The circadian clock is a critical regulator of biological functions controlling behavioral, physiological and biochemical processes. Because the liver is the primary regulator of metabolites within the mammalian body and the disruption of circadian rhythms in liver is associated with severe illness, circadian regulators would play a strong role in maintaining liver function. However, the regulatory structure that governs circadian dynamics within the liver at a transcriptional level remains unknown. To explore this aspect, we analyzed hepatic transcriptional dynamics in Sprague-Dawley rats over a period of 24 hours to assess the genome-wide responses.'),
(96052, 2014, 'bmc', 'openBEB: open biological experiment browser for correlative measurements', 'Ramakrishnan, Chandrasekhar|Bieri, Andrej|Sauter, Nora|Roizard, Sophie|Ringler, Philippe|Müller, Shirley A|Goldie, Kenneth N|Enimanev, Kaloyan|Stahlberg, Henning|Rinn, Bernd|Braun, Thomas', 'Chemical and Biochemical Engineering Department, Rutgers the State University of New Jersey, Piscataway, NJ 08854, USA. yannis@rci.rutgers.edu.|Chemical and Biochemical Engineering Department, Rutgers the State University of New Jersey, Piscataway, NJ 08854, USA. yannis@rci.rutgers.edu.|Chemical and Biochemical Engineering Department, Rutgers the State University of New Jersey, Piscataway, NJ 08854, USA. yannis@rci.rutgers.edu.|Chemical and Biochemical Engineering Department, Rutgers the State University of New Jersey, Piscataway, NJ 08854, USA. yannis@rci.rutgers.edu.|Chemical and Biochemical Engineering Department, Rutgers the State University of New Jersey, Piscataway, NJ 08854, USA. yannis@rci.rutgers.edu.|Chemical and Biochemical Engineering Department, Rutgers the State University of New Jersey, Piscataway, NJ 08854, USA. yannis@rci.rutgers.edu.|Chemical and Biochemical Engineering Department, Rutgers the State University of New Jersey, Piscataway, NJ 08854, USA. yannis@rci.rutgers.edu.|Chemical and Biochemical Engineering Department, Rutgers the State University of New Jersey, Piscataway, NJ 08854, USA. yannis@rci.rutgers.edu.|Chemical and Biochemical Engineering Department, Rutgers the State University of New Jersey, Piscataway, NJ 08854, USA. yannis@rci.rutgers.edu.|Chemical and Biochemical Engineering Department, Rutgers the State University of New Jersey, Piscataway, NJ 08854, USA. yannis@rci.rutgers.edu.|Center for Cellular Imaging and NanoAnalytics (C-CINA), Biozentrum, Universität Basel, Basel, Switzerland. Thomas.Braun@unibas.ch.', 'Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Switzerland', 7, 'Automation, Laboratory|Computer Simulation|Software Design|Systems Biology', 'Journal Article', '10.1186/1471-2105-15-84', '24666611', 'New experimental methods must be developed to study interaction networks in systems biology. To reduce biological noise, individual subjects, such as single cells, should be analyzed using high throughput approaches. The measurement of several correlative physical properties would further improve data consistency. Accordingly, a considerable quantity of data must be acquired, correlated, catalogued and stored in a database for subsequent analysis.'),
(96053, 2014, 'bmc', 'FreeContact: fast and free software for protein contact prediction from residue co-evolution', 'Kaján, László|Hopf, Thomas A|Kalaš, Matúš|Marks, Debora S|Rost, Burkhard', 'Center for Cellular Imaging and NanoAnalytics (C-CINA), Biozentrum, Universität Basel, Basel, Switzerland. Thomas.Braun@unibas.ch.|Center for Cellular Imaging and NanoAnalytics (C-CINA), Biozentrum, Universität Basel, Basel, Switzerland. Thomas.Braun@unibas.ch.|Center for Cellular Imaging and NanoAnalytics (C-CINA), Biozentrum, Universität Basel, Basel, Switzerland. Thomas.Braun@unibas.ch.|Center for Cellular Imaging and NanoAnalytics (C-CINA), Biozentrum, Universität Basel, Basel, Switzerland. Thomas.Braun@unibas.ch.|Department for Bioinformatics and Computational Biology, TU Munich, Boltzmannstraße 3, Garching 85748, Germany. assistant@rostlab.org.', 'Switzerland|Switzerland|Switzerland|Switzerland|Germany', 0, 'Algorithms|Computational Biology|Protein Conformation|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-15-85', '24669753', '20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions of protein three-dimensional structure. The method EVfold broke new ground using mean-field Direct Coupling Analysis (EVfold-mfDCA), the method PSICOV applied a related concept by estimating a sparse inverse covariance matrix. Both methods (EVfold-mfDCA and PSICOV) are publicly available, but both require too much CPU time for interactive applications. On top, EVfold-mfDCA depends on proprietary software.'),
(96054, 2014, 'bmc', 'A graph theoretic approach to utilizing protein structure to identify non-random somatic mutations', 'Ryslik, Gregory A|Cheng, Yuwei|Cheung, Kei-Hoi|Modis, Yorgo|Zhao, Hongyu', 'Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.', 'United States|United States|United States|United States|United States', 18, 'Cluster Analysis|Genes, Neoplasm|Mutation|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1186/1471-2105-15-86', '24669769', 'It is well known that the development of cancer is caused by the accumulation of somatic mutations within the genome. For oncogenes specifically, current research suggests that there is a small set of driver mutations that are primarily responsible for tumorigenesis. Further, due to recent pharmacological successes in treating these driver mutations and their resulting tumors, a variety of approaches have been developed to identify potential driver mutations using methods such as machine learning and mutational clustering. We propose a novel methodology that increases our power to identify mutational clusters by taking into account protein tertiary structure via a graph theoretical approach.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96055, 2014, 'bmc', 'Estimation of protein function using template-based alignment of enzyme active sites', 'Hanson, Brett|Westin, Charles|Rosa, Mario|Grier, Alexander|Osipovitch, Mikhail|MacDonald, Madolyn L|Dodge, Greg|Boli, Paule M|Corwin, Cyprian W|Kessler, Haeja|McKay, Talia|Bernstein, Herbert J|Craig, Paul A', 'Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Rochester Institute of Technology, School of Chemistry & Materials Science, 1 Lomb Memorial Drive, Rochester, NY 14623, USA. paul.craig@rit.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', 0, 'Algorithms|Catalytic Domain|Models, Molecular|Protein Structure, Tertiary|Proteins|Software|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-15-87', '24669788', 'The accumulation of protein structural data occurs more rapidly than it can be characterized by traditional laboratory means. This has motivated widespread efforts to predict enzyme function computationally. The most useful/accurate strategies employed to date are based on the detection of motifs in novel structures that correspond to a specific function. Functional residues are critical components of predictively useful motifs. We have implemented a novel method, to complement current approaches, which detects motifs solely on the basis of distance restraints between catalytic residues.'),
(96056, 2014, 'bmc', 'Multi-model inference using mixed effects from a linear regression based genetic algorithm', 'Van der Borght, Koen|Verbeke, Geert|van Vlijmen, Herman', 'Janssen Infectious Diseases-Diagnostics BVBA, B-2340 Beerse, Belgium. kvdborgh@its.jnj.com.|Janssen Infectious Diseases-Diagnostics BVBA, B-2340 Beerse, Belgium. kvdborgh@its.jnj.com.|Janssen Infectious Diseases-Diagnostics BVBA, B-2340 Beerse, Belgium. kvdborgh@its.jnj.com.', 'Belgium|Belgium|Belgium', 3, 'Algorithms|Computational Biology|Databases, Genetic|Drug Resistance, Viral|HIV-1|Humans|Least-Squares Analysis|Linear Models|Models, Genetic|Mutation|Phenotype|Pyrrolidinones|Raltegravir Potassium', 'Journal Article', '10.1186/1471-2105-15-88', '24669828', 'Different high-dimensional regression methodologies exist for the selection of variables to predict a continuous variable. To improve the variable selection in case clustered observations are present in the training data, an extension towards mixed-effects modeling (MM) is requested, but may not always be straightforward to implement.In this article, we developed such a MM extension (GA-MM-MMI) for the automated variable selection by a linear regression based genetic algorithm (GA) using multi-model inference (MMI). We exemplify our approach by training a linear regression model for prediction of resistance to the integrase inhibitor Raltegravir (RAL) on a genotype-phenotype database, with many integrase mutations as candidate covariates. The genotype-phenotype pairs in this database were derived from a limited number of subjects, with presence of multiple data points from the same subject, and with an intra-class correlation of 0.92.'),
(96057, 2014, 'bmc', 'TSSAR: TSS annotation regime for dRNA-seq data', 'Amman, Fabian|Wolfinger, Michael T|Lorenz, Ronny|Hofacker, Ivo L|Stadler, Peter F|Findeiß, Sven', 'Bioinformatics Group, Department of Computer Science and the Interdisciplinary Center for Bioinformatic, University of Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany. afabian@bioinf.uni-leipzig.de.|Bioinformatics Group, Department of Computer Science and the Interdisciplinary Center for Bioinformatic, University of Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany. afabian@bioinf.uni-leipzig.de.|Bioinformatics Group, Department of Computer Science and the Interdisciplinary Center for Bioinformatic, University of Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany. afabian@bioinf.uni-leipzig.de.|Bioinformatics Group, Department of Computer Science and the Interdisciplinary Center for Bioinformatic, University of Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany. afabian@bioinf.uni-leipzig.de.|Bioinformatics Group, Department of Computer Science and the Interdisciplinary Center for Bioinformatic, University of Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany. afabian@bioinf.uni-leipzig.de.|Bioinformatics Group, Department of Computer Science and the Interdisciplinary Center for Bioinformatic, University of Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany. afabian@bioinf.uni-leipzig.de.', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Base Sequence|Databases, Nucleic Acid|Genome|Genomics|Helicobacter pylori|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, RNA|Software|Stenotrophomonas maltophilia', 'Journal Article', '10.1186/1471-2105-15-89', '24674136', 'Differential RNA sequencing (dRNA-seq) is a high-throughput screening technique designed to examine the architecture of bacterial operons in general and the precise position of transcription start sites (TSS) in particular. Hitherto, dRNA-seq data were analyzed by visualizing the sequencing reads mapped to the reference genome and manually annotating reliable positions. This is very labor intensive and, due to the subjectivity, biased.'),
(96058, 2014, 'bmc', 'Consistency of metagenomic assignment programs in simulated and real data', 'Garcia-Etxebarria, Koldo|Garcia-Garcerà, Marc|Calafell, Francesc', 'Bioinformatics Group, Department of Computer Science and the Interdisciplinary Center for Bioinformatic, University of Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany. afabian@bioinf.uni-leipzig.de.|Bioinformatics Group, Department of Computer Science and the Interdisciplinary Center for Bioinformatic, University of Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany. afabian@bioinf.uni-leipzig.de.|Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Barcelona, Spain. francesc.calafell@upf.edu.', 'Germany|Germany|Spain', 13, 'Algorithms|Animals|Bayes Theorem|Genome|Metagenomics|Mice|Mice, Inbred C57BL|Reproducibility of Results|Skin', 'Journal Article', '10.1186/1471-2105-15-90', '24678591', 'Metagenomics is the genomic study of uncultured environmental samples, which has been greatly facilitated by the advent of shotgun-sequencing technologies. One of the main focuses of metagenomics is the discovery of previously uncultured microorganisms, which makes the assignment of sequences to a particular taxon a challenge and a crucial step. Recently, several methods have been developed to perform this task, based on different methodologies such as sequence composition or sequence similarity. The sequence composition methods have the ability to completely assign the whole dataset. However, their use in metagenomics and the study of their performance with real data is limited. In this work, we assess the consistency of three different methods (BLAST + Lowest Common Ancestor, Phymm, and Naïve Bayesian Classifier) in assigning real and simulated sequence reads.'),
(96059, 2014, 'bmc', 'Differential meta-analysis of RNA-seq data from multiple studies', 'Rau, Andrea|Marot, Guillemette|Jaffrézic, Florence', 'INRA, UMR1313 Génétique animale et biologie intégrative, 78352 Jouy-en-Josas, France. andrea.rau@jouy.inra.fr.|INRA, UMR1313 Génétique animale et biologie intégrative, 78352 Jouy-en-Josas, France. andrea.rau@jouy.inra.fr.|INRA, UMR1313 Génétique animale et biologie intégrative, 78352 Jouy-en-Josas, France. andrea.rau@jouy.inra.fr.', 'France|France|France', 29, 'Cell Line, Tumor|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-15-91', '24678608', 'High-throughput sequencing is now regularly used for studies of the transcriptome (RNA-seq), particularly for comparisons among experimental conditions. For the time being, a limited number of biological replicates are typically considered in such experiments, leading to low detection power for differential expression. As their cost continues to decrease, it is likely that additional follow-up studies will be conducted to re-address the same biological question.'),
(96060, 2014, 'bmc', 'The number of reduced alignments between two DNA sequences', 'Andrade, Helena|Area, Iván|Nieto, Juan J|Torres, Angela', 'INRA, UMR1313 Génétique animale et biologie intégrative, 78352 Jouy-en-Josas, France. andrea.rau@jouy.inra.fr.|INRA, UMR1313 Génétique animale et biologie intégrative, 78352 Jouy-en-Josas, France. andrea.rau@jouy.inra.fr.|Departamento de Análise Matemática, Facultade de Matemáticas, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain. juanjose.nieto.roig@usc.es.|Departamento de Análise Matemática, Facultade de Matemáticas, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain. juanjose.nieto.roig@usc.es.', 'France|France|Spain|Spain', 0, 'Base Sequence|DNA|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-15-94', '24684679', 'In this study we consider DNA sequences as mathematical strings. Total and reduced alignments between two DNA sequences have been considered in the literature to measure their similarity. Results for explicit representations of some alignments have been already obtained.'),
(96061, 2014, 'bmc', 'DAFS: a data-adaptive flag method for RNA-sequencing data to differentiate genes with low and high expression', 'George, Nysia I|Chang, Ching-Wei', 'Departamento de Análise Matemática, Facultade de Matemáticas, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain. juanjose.nieto.roig@usc.es.|Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. Ching-Wei.Chang@fda.hhs.gov.', 'Spain|United States', 12, 'Algorithms|Animals|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Mice|RNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-15-92', '24685233', 'Next-generation sequencing (NGS) has advanced the application of high-throughput sequencing technologies in genetic and genomic variation analysis. Due to the large dynamic range of expression levels, RNA-seq is more prone to detect transcripts with low expression. It is clear that genes with no mapped reads are not expressed, however, there is ongoing debate about the level of abundance that constitutes biologically meaningful expression. To date, there is no consensus on the definition of low expression. Since random variation is high in regions with low expression and distributions of transcript expression are affected by numerous experimental factors, methods to differentiate low and high expressed data in a sample are critical to interpreting classes of abundance levels in RNA-seq data.'),
(96062, 2014, 'bmc', 'SPiCE: a web-based tool for sequence-based protein classification and exploration', 'van den Berg, Bastiaan A|Reinders, Marcel J T|Roubos, Johannes A|de Ridder, Dick', 'Delft Bioinformatics Lab, Department of Intelligent Systems, Faculty Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, 2628CD, Delft, The Netherlands. b.a.vandenberg@tudelft.nl.|Delft Bioinformatics Lab, Department of Intelligent Systems, Faculty Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, 2628CD, Delft, The Netherlands. b.a.vandenberg@tudelft.nl.|Delft Bioinformatics Lab, Department of Intelligent Systems, Faculty Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, 2628CD, Delft, The Netherlands. b.a.vandenberg@tudelft.nl.|Delft Bioinformatics Lab, Department of Intelligent Systems, Faculty Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, 2628CD, Delft, The Netherlands. b.a.vandenberg@tudelft.nl.', 'Netherlands|Netherlands|Netherlands|Netherlands', 8, 'Algorithms|Amino Acid Sequence|Aspergillus niger|Internet|Molecular Sequence Data|Proteins|Saccharomyces cerevisiae|Sequence Analysis, Protein|Software Design', 'Journal Article', '10.1186/1471-2105-15-93', '24685258', 'Amino acid sequences and features extracted from such sequences have been used to predict many protein properties, such as subcellular localization or solubility, using classifier algorithms. Although software tools are available for both feature extraction and classifier construction, their application is not straightforward, requiring users to install various packages and to convert data into different formats. This lack of easily accessible software hampers quick, explorative use of sequence-based classification techniques by biologists.'),
(96063, 2014, 'bmc', 'A local average distance descriptor for flexible protein structure comparison', 'Wang, Hsin-Wei|Chu, Chia-Han|Wang, Wen-Ching|Pai, Tun-Wen', 'Delft Bioinformatics Lab, Department of Intelligent Systems, Faculty Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, 2628CD, Delft, The Netherlands. b.a.vandenberg@tudelft.nl.|Delft Bioinformatics Lab, Department of Intelligent Systems, Faculty Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, 2628CD, Delft, The Netherlands. b.a.vandenberg@tudelft.nl.|Delft Bioinformatics Lab, Department of Intelligent Systems, Faculty Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, 2628CD, Delft, The Netherlands. b.a.vandenberg@tudelft.nl.|Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung, Taiwan. twp@mail.ntou.edu.tw.', 'Netherlands|Netherlands|Netherlands|-', 0, 'Algorithms|Databases, Protein|Models, Molecular|Protein Structure, Tertiary|Proteins|Structural Homology, Protein', 'Comparative Study', '10.1186/1471-2105-15-95', '24694083', 'Protein structures are flexible and often show conformational changes upon binding to other molecules to exert biological functions. As protein structures correlate with characteristic functions, structure comparison allows classification and prediction of proteins of undefined functions. However, most comparison methods treat proteins as rigid bodies and cannot retrieve similarities of proteins with large conformational changes effectively.'),
(96064, 2014, 'bmc', 'Quantum coupled mutation finder: predicting functionally or structurally important sites in proteins using quantum Jensen-Shannon divergence and CUDA programming', 'Gültas, Mehmet|Düzgün, Güncel|Herzog, Sebastian|Jäger, Sven Joachim|Meckbach, Cornelia|Wingender, Edgar|Waack, Stephan', 'Institute of Computer Science, University of Göttingen, Goldschmidtstr, 7, 37077 Göttingen, Germany. waack@cs.uni-goettingen.de.|Institute of Computer Science, University of Göttingen, Goldschmidtstr, 7, 37077 Göttingen, Germany. waack@cs.uni-goettingen.de.|Institute of Computer Science, University of Göttingen, Goldschmidtstr, 7, 37077 Göttingen, Germany. waack@cs.uni-goettingen.de.|Institute of Computer Science, University of Göttingen, Goldschmidtstr, 7, 37077 Göttingen, Germany. waack@cs.uni-goettingen.de.|Institute of Computer Science, University of Göttingen, Goldschmidtstr, 7, 37077 Göttingen, Germany. waack@cs.uni-goettingen.de.|Institute of Computer Science, University of Göttingen, Goldschmidtstr, 7, 37077 Göttingen, Germany. waack@cs.uni-goettingen.de.|Institute of Computer Science, University of Göttingen, Goldschmidtstr, 7, 37077 Göttingen, Germany. waack@cs.uni-goettingen.de.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Amino Acid Sequence|Amino Acids|Conserved Sequence|ErbB Receptors|Glucokinase|Humans|Mutation|Protein Conformation|Proteins|Quantum Theory|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-15-96', '24694117', 'The identification of functionally or structurally important non-conserved residue sites in protein MSAs is an important challenge for understanding the structural basis and molecular mechanism of protein functions. Despite the rich literature on compensatory mutations as well as sequence conservation analysis for the detection of those important residues, previous methods often rely on classical information-theoretic measures. However, these measures usually do not take into account dis/similarities of amino acids which are likely to be crucial for those residues. In this study, we present a new method, the Quantum Coupled Mutation Finder (QCMF) that incorporates significant dis/similar amino acid pair signals in the prediction of functionally or structurally important sites.'),
(96065, 2014, 'bmc', 'Multi-TGDR, a multi-class regularization method, identifies the metabolic profiles of hepatocellular carcinoma and cirrhosis infected with hepatitis B or hepatitis C virus', 'Tian, Suyan|Chang, Howard H|Wang, Chi|Jiang, Jing|Wang, Xiaomei|Niu, Junqi', 'Division of Clinical Epidemiology, First Hospital of the Jilin University, 71Xinmin Street, Changchun, Jilin 130021, China. stian@rockefeller.edu.|Division of Clinical Epidemiology, First Hospital of the Jilin University, 71Xinmin Street, Changchun, Jilin 130021, China. stian@rockefeller.edu.|Division of Clinical Epidemiology, First Hospital of the Jilin University, 71Xinmin Street, Changchun, Jilin 130021, China. stian@rockefeller.edu.|Division of Clinical Epidemiology, First Hospital of the Jilin University, 71Xinmin Street, Changchun, Jilin 130021, China. stian@rockefeller.edu.|Division of Clinical Epidemiology, First Hospital of the Jilin University, 71Xinmin Street, Changchun, Jilin 130021, China. stian@rockefeller.edu.|Division of Clinical Epidemiology, First Hospital of the Jilin University, 71Xinmin Street, Changchun, Jilin 130021, China. stian@rockefeller.edu.', 'China|China|China|China|China|China', 9, 'Carcinoma, Hepatocellular|Hepatitis B|Hepatitis C|Humans|Liver Neoplasms|Metabolome|Metabolomics', 'Journal Article', '10.1186/1471-2105-15-97', '24707821', 'Over the last decade, metabolomics has evolved into a mainstream enterprise utilized by many laboratories globally. Like other omics data, metabolomics data has the characteristics of a smaller sample size compared to the number of features evaluated. Thus the selection of an optimal subset of features with a supervised classifier is imperative. We extended an existing feature selection algorithm, threshold gradient descent regularization (TGDR), to handle multi-class classification of omics data, and proposed two such extensions referred to as multi-TGDR. Both multi-TGDR frameworks were used to analyze a metabolomics dataset that compares the metabolic profiles of hepatocellular carcinoma (HCC) infected with hepatitis B (HBV) or C virus (HCV) with that of cirrhosis induced by HBV/HCV infection, the goal was to improve early-stage diagnosis of HCC.'),
(96066, 2014, 'bmc', 'TOPS: a versatile software tool for statistical analysis and visualization of combinatorial gene-gene and gene-drug interaction screens', 'Muellner, Markus K|Duernberger, Gerhard|Ganglberger, Florian|Kerzendorfer, Claudia|Uras, Iris Z|Schoenegger, Andreas|Bagienski, Klaudia|Colinge, Jacques|Nijman, Sebastian M B', 'Research Center for Molecular Medicine of the Austrian Academy of Sciences (CeMM), Vienna, Austria. mmuellner@cemm.oeaw.ac.at.|Research Center for Molecular Medicine of the Austrian Academy of Sciences (CeMM), Vienna, Austria. mmuellner@cemm.oeaw.ac.at.|Research Center for Molecular Medicine of the Austrian Academy of Sciences (CeMM), Vienna, Austria. mmuellner@cemm.oeaw.ac.at.|Research Center for Molecular Medicine of the Austrian Academy of Sciences (CeMM), Vienna, Austria. mmuellner@cemm.oeaw.ac.at.|Research Center for Molecular Medicine of the Austrian Academy of Sciences (CeMM), Vienna, Austria. mmuellner@cemm.oeaw.ac.at.|Research Center for Molecular Medicine of the Austrian Academy of Sciences (CeMM), Vienna, Austria. mmuellner@cemm.oeaw.ac.at.|Research Center for Molecular Medicine of the Austrian Academy of Sciences (CeMM), Vienna, Austria. mmuellner@cemm.oeaw.ac.at.|Research Center for Molecular Medicine of the Austrian Academy of Sciences (CeMM), Vienna, Austria. mmuellner@cemm.oeaw.ac.at.|Research Center for Molecular Medicine of the Austrian Academy of Sciences (CeMM), Vienna, Austria. mmuellner@cemm.oeaw.ac.at.', 'Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria', 0, 'Algorithms|Breast Neoplasms|Cell Line, Tumor|Computer Graphics|Data Interpretation, Statistical|Drug Evaluation, Preclinical|Female|Genes|Genomics|High-Throughput Nucleotide Sequencing|Humans|Linear Models|RNA Interference|Software', 'Journal Article', '10.1186/1471-2105-15-98', '24712852', 'Measuring the impact of combinations of genetic or chemical perturbations on cellular fitness, sometimes referred to as synthetic lethal screening, is a powerful method for obtaining novel insights into gene function and drug action. Especially when performed at large scales, gene-gene or gene-drug interaction screens can reveal complex genetic interactions or drug mechanism of action or even identify novel therapeutics for the treatment of diseases.The result of such large-scale screen results can be represented as a matrix with a numeric score indicating the cellular fitness (e.g. viability or doubling time) for each double perturbation. In a typical screen, the majority of combinations do not impact the cellular fitness. Thus, it is critical to first discern true hits from noise. Subsequent data exploration and visualization methods can assist to extract meaningful biological information from the data. However, despite the increasing interest in combination perturbation screens, no user friendly open-source program exists that combines statistical analysis, data exploration tools and visualization.'),
(96067, 2014, 'bmc', 'Genome alignment with graph data structures: a comparison', 'Kehr, Birte|Trappe, Kathrin|Holtgrewe, Manuel|Reinert, Knut', 'Department of Computer Science, Freie Universität Berlin, Takustr, 9, 14195 Berlin, Germany. birte.kehr@fu-berlin.de.|Department of Computer Science, Freie Universität Berlin, Takustr, 9, 14195 Berlin, Germany. birte.kehr@fu-berlin.de.|Department of Computer Science, Freie Universität Berlin, Takustr, 9, 14195 Berlin, Germany. birte.kehr@fu-berlin.de.|Department of Computer Science, Freie Universität Berlin, Takustr, 9, 14195 Berlin, Germany. birte.kehr@fu-berlin.de.', 'Germany|Germany|Germany|Germany', 18, 'Algorithms|Computer Graphics|Genome|Genomics|Sequence Alignment', 'Comparative Study', '10.1186/1471-2105-15-99', '24712884', 'Recent advances in rapid, low-cost sequencing have opened up the opportunity to study complete genome sequences. The computational approach of multiple genome alignment allows investigation of evolutionarily related genomes in an integrated fashion, providing a basis for downstream analyses such as rearrangement studies and phylogenetic inference.Graphs have proven to be a powerful tool for coping with the complexity of genome-scale sequence alignments. The potential of graphs to intuitively represent all aspects of genome alignments led to the development of graph-based approaches for genome alignment. These approaches construct a graph from a set of local alignments, and derive a genome alignment through identification and removal of graph substructures that indicate errors in the alignment.'),
(96068, 2014, 'bmc', 'Adaptable probabilistic mapping of short reads using position specific scoring matrices', 'Kerpedjiev, Peter|Frellsen, Jes|Lindgreen, Stinus|Krogh, Anders', 'Department of Computer Science, Freie Universität Berlin, Takustr, 9, 14195 Berlin, Germany. birte.kehr@fu-berlin.de.|Department of Computer Science, Freie Universität Berlin, Takustr, 9, 14195 Berlin, Germany. birte.kehr@fu-berlin.de.|Department of Computer Science, Freie Universität Berlin, Takustr, 9, 14195 Berlin, Germany. birte.kehr@fu-berlin.de.|Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen, Denmark. krogh@binf.ku.dk.', 'Germany|Germany|Germany|Denmark', 0, 'Animals|Drosophila|Evolution, Molecular|Genome|Humans|Position-Specific Scoring Matrices|Probability|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-15-100', '24717095', 'Modern DNA sequencing methods produce vast amounts of data that often requires mapping to a reference genome. Most existing programs use the number of mismatches between the read and the genome as a measure of quality. This approach is without a statistical foundation and can for some data types result in many wrongly mapped reads. Here we present a probabilistic mapping method based on position-specific scoring matrices, which can take into account not only the quality scores of the reads but also user-specified models of evolution and data-specific biases.'),
(96069, 2014, 'bmc', 'Improving clustering with metabolic pathway data', 'Milone, Diego H|Stegmayer, Georgina|López, Mariana|Kamenetzky, Laura|Carrari, Fernando', 'Research Center for Signals, Systems and Computational Intelligence, sinc(i), FICH-UNL, CONICET, Ciudad Universitaria UNL, (3000) Santa Fe, Argentina. d.milone@ieee.org.|Research Center for Signals, Systems and Computational Intelligence, sinc(i), FICH-UNL, CONICET, Ciudad Universitaria UNL, (3000) Santa Fe, Argentina. d.milone@ieee.org.|Research Center for Signals, Systems and Computational Intelligence, sinc(i), FICH-UNL, CONICET, Ciudad Universitaria UNL, (3000) Santa Fe, Argentina. d.milone@ieee.org.|Research Center for Signals, Systems and Computational Intelligence, sinc(i), FICH-UNL, CONICET, Ciudad Universitaria UNL, (3000) Santa Fe, Argentina. d.milone@ieee.org.|Research Center for Signals, Systems and Computational Intelligence, sinc(i), FICH-UNL, CONICET, Ciudad Universitaria UNL, (3000) Santa Fe, Argentina. d.milone@ieee.org.', 'Argentina|Argentina|Argentina|Argentina|Argentina', 7, 'Algorithms|Arabidopsis|Cluster Analysis|Data Mining|Lycopersicon esculentum|Metabolic Networks and Pathways|Programming Languages', 'Journal Article', '10.1186/1471-2105-15-101', '24717120', 'It is a common practice in bioinformatics to validate each group returned by a clustering algorithm through manual analysis, according to a-priori biological knowledge. This procedure helps finding functionally related patterns to propose hypotheses for their behavior and the biological processes involved. Therefore, this knowledge is used only as a second step, after data are just clustered according to their expression patterns. Thus, it could be very useful to be able to improve the clustering of biological data by incorporating prior knowledge into the cluster formation itself, in order to enhance the biological value of the clusters.'),
(96070, 2014, 'bmc', 'Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering', 'Guo, Xuan|Meng, Yu|Yu, Ning|Pan, Yi', 'Research Center for Signals, Systems and Computational Intelligence, sinc(i), FICH-UNL, CONICET, Ciudad Universitaria UNL, (3000) Santa Fe, Argentina. d.milone@ieee.org.|Research Center for Signals, Systems and Computational Intelligence, sinc(i), FICH-UNL, CONICET, Ciudad Universitaria UNL, (3000) Santa Fe, Argentina. d.milone@ieee.org.|Research Center for Signals, Systems and Computational Intelligence, sinc(i), FICH-UNL, CONICET, Ciudad Universitaria UNL, (3000) Santa Fe, Argentina. d.milone@ieee.org.|Department of Computer Science, Georgia State University, 34 Peachtree Street, Atlanta, USA. yipan@gsu.edu.', 'Argentina|Argentina|Argentina|Georgia', 48, 'Algorithms|Cluster Analysis|Epistasis, Genetic|Genetic Loci|Genome|Genome-Wide Association Study|Genotype|Phenotype|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-15-102', '24717145', 'Taking the advantage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger.'),
(96071, 2014, 'bmc', 'Improved multi-level protein-protein interaction prediction with semantic-based regularization', 'Saccà, Claudio|Teso, Stefano|Diligenti, Michelangelo|Passerini, Andrea', 'Department of Computer Science, Georgia State University, 34 Peachtree Street, Atlanta, USA. yipan@gsu.edu.|Department of Computer Science, Georgia State University, 34 Peachtree Street, Atlanta, USA. yipan@gsu.edu.|Department of Computer Science, Georgia State University, 34 Peachtree Street, Atlanta, USA. yipan@gsu.edu.|Dipartimento di Ingegneria e Scienza dellInformazione, University of Trento, Trento, Italy. passerini@disi.unitn.it.', 'Georgia|Georgia|Georgia|Italy', 8, 'Artificial Intelligence|Models, Molecular|Protein Binding|Protein Interaction Domains and Motifs|Proteins|Semantics|Software', 'Journal Article', '10.1186/1471-2105-15-103', '24725682', 'Protein-protein interactions can be seen as a hierarchical process occurring at three related levels: proteins bind by means of specific domains, which in turn form interfaces through patches of residues. Detailed knowledge about which domains and residues are involved in a given interaction has extensive applications to biology, including better understanding of the binding process and more efficient drug/enzyme design. Alas, most current interaction prediction methods do not identify which parts of a protein actually instantiate an interaction. Furthermore, they also fail to leverage the hierarchical nature of the problem, ignoring otherwise useful information available at the lower levels, when they do, they do not generate predictions that are guaranteed to be consistent between levels.'),
(96072, 2014, 'bmc', 'BAYSIC: a Bayesian method for combining sets of genome variants with improved specificity and sensitivity', 'Cantarel, Brandi L|Weaver, Daniel|McNeill, Nathan|Zhang, Jianhua|Mackey, Aaron J|Reese, Justin', 'Dipartimento di Ingegneria e Scienza dellInformazione, University of Trento, Trento, Italy. passerini@disi.unitn.it.|Dipartimento di Ingegneria e Scienza dellInformazione, University of Trento, Trento, Italy. passerini@disi.unitn.it.|Dipartimento di Ingegneria e Scienza dellInformazione, University of Trento, Trento, Italy. passerini@disi.unitn.it.|Dipartimento di Ingegneria e Scienza dellInformazione, University of Trento, Trento, Italy. passerini@disi.unitn.it.|Dipartimento di Ingegneria e Scienza dellInformazione, University of Trento, Trento, Italy. passerini@disi.unitn.it.|Genformatic, LLC, Austin, TX 78731, USA. jreese@genformatic.com.', 'Italy|Italy|Italy|Italy|Italy|United States', 30, 'Algorithms|Bayes Theorem|Exome|Genome, Human|Humans|Mutation|Polymorphism, Single Nucleotide|Probability|Software Design', 'Journal Article', '10.1186/1471-2105-15-104', '24725768', 'Accurate genomic variant detection is an essential step in gleaning medically useful information from genome data. However, low concordance among variant-calling methods reduces confidence in the clinical validity of whole genome and exome sequence data, and confounds downstream analysis for applications in genome medicine.Here we describe BAYSIC (BAYeSian Integrated Caller), which combines SNP variant calls produced by different methods (e.g. GATK, FreeBayes, Atlas, SamTools, etc.) into a more accurate set of variant calls. BAYSIC differs from majority voting, consensus or other ad hoc intersection-based schemes for combining sets of genome variant calls. Unlike other classification methods, the underlying BAYSIC model does not require training using a gold standard of true positives. Rather, with each new dataset, BAYSIC performs an unsupervised, fully Bayesian latent class analysis to estimate false positive and false negative error rates for each input method. The user specifies a posterior probability threshold according to the users tolerance for false positive and false negative errors, lowering the posterior probability threshold allows the user to trade specificity for sensitivity while raising the threshold increases specificity in exchange for sensitivity.'),
(96073, 2014, 'bmc', 'dRiskKB: a large-scale disease-disease risk relationship knowledge base constructed from biomedical text', 'Xu, Rong|Li, Li|Wang, Quanqiu', 'Medical Informatics Division, Case Western Reserve University, Cleveland, OH, USA. rxx@case.edu.|Medical Informatics Division, Case Western Reserve University, Cleveland, OH, USA. rxx@case.edu.|Medical Informatics Division, Case Western Reserve University, Cleveland, OH, USA. rxx@case.edu.', 'United States|United States|United States', 23, 'Algorithms|Diabetes Mellitus, Type 2|Drug Repositioning|Humans|Knowledge Bases|MEDLINE|Obesity|Pattern Recognition, Automated|Phenotype|Risk Factors', 'Journal Article', '10.1186/1471-2105-15-105', '24725842', 'Discerning the genetic contributions to complex human diseases is a challenging mandate that demands new types of data and calls for new avenues for advancing the state-of-the-art in computational approaches to uncovering disease etiology. Systems approaches to studying observable phenotypic relationships among diseases are emerging as an active area of research for both novel disease gene discovery and drug repositioning. Currently, systematic study of disease relationships on a phenome-wide scale is limited due to the lack of large-scale machine understandable disease phenotype relationship knowledge bases. Our study innovates a semi-supervised iterative pattern learning approach that is used to build an precise, large-scale disease-disease risk relationship (D1 xe2x86x92 D2) knowledge base (dRiskKB) from a vast corpus of free-text published biomedical literature.'),
(96074, 2014, 'bmc', 'Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes', 'Somfai, Gábor Márk|Tátrai, Erika|Laurik, Lenke|Varga, Boglárka|Ölvedy, Veronika|Jiang, Hong|Wang, Jianhua|Smiddy, William E|Somogyi, Anikó|DeBuc, Delia Cabrera', 'Medical Informatics Division, Case Western Reserve University, Cleveland, OH, USA. rxx@case.edu.|Medical Informatics Division, Case Western Reserve University, Cleveland, OH, USA. rxx@case.edu.|Medical Informatics Division, Case Western Reserve University, Cleveland, OH, USA. rxx@case.edu.|Medical Informatics Division, Case Western Reserve University, Cleveland, OH, USA. rxx@case.edu.|Medical Informatics Division, Case Western Reserve University, Cleveland, OH, USA. rxx@case.edu.|Medical Informatics Division, Case Western Reserve University, Cleveland, OH, USA. rxx@case.edu.|Medical Informatics Division, Case Western Reserve University, Cleveland, OH, USA. rxx@case.edu.|Medical Informatics Division, Case Western Reserve University, Cleveland, OH, USA. rxx@case.edu.|Medical Informatics Division, Case Western Reserve University, Cleveland, OH, USA. rxx@case.edu.|Miller School of Medicine, Bascom Palmer Eye Institute, University of Miami, 1638 NW Tenth Avenue, Miami, FL 33136, USA. dcabrera2@med.miami.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 12, 'Adult|Automation|Bayes Theorem|Diabetic Retinopathy|Early Diagnosis|Female|Humans|Male|Tomography, Optical Coherence', 'Journal Article', '10.1186/1471-2105-15-106', '24725911', 'Artificial neural networks (ANNs) have been used to classify eye diseases, such as diabetic retinopathy (DR) and glaucoma. DR is the leading cause of blindness in working-age adults in the developed world. The implementation of DR diagnostic routines could be feasibly improved by the integration of structural and optical property test measurements of the retinal structure that provide important and complementary information for reaching a diagnosis. In this study, we evaluate the capability of several structural and optical features (thickness, total reflectance and fractal dimension) of various intraretinal layers extracted from optical coherence tomography images to train a Bayesian ANN to discriminate between healthy and diabetic eyes with and with no mild retinopathy.'),
(96075, 2014, 'bmc', 'MUBII-TB-DB: a database of mutations associated with antibiotic resistance in Mycobacterium tuberculosis', 'Flandrois, Jean-Pierre|Lina, Gérard|Dumitrescu, Oana', 'Laboratoire de Biométrie et Biologie Évolutive, UMR CNRS 5558, Université Claude Bernard - Lyon 1, 43 bd, du 11 Novembre 1918, 69622 Villeurbanne Cedex, France. jp.flandrois@univ-lyon1.fr.|Laboratoire de Biométrie et Biologie Évolutive, UMR CNRS 5558, Université Claude Bernard - Lyon 1, 43 bd, du 11 Novembre 1918, 69622 Villeurbanne Cedex, France. jp.flandrois@univ-lyon1.fr.|Laboratoire de Biométrie et Biologie Évolutive, UMR CNRS 5558, Université Claude Bernard - Lyon 1, 43 bd, du 11 Novembre 1918, 69622 Villeurbanne Cedex, France. jp.flandrois@univ-lyon1.fr.', 'France|France|France', 45, 'Antitubercular Agents|Base Sequence|DNA, Bacterial|Databases, Genetic|Drug Resistance, Bacterial|Humans|Molecular Sequence Data|Mutation|Mycobacterium tuberculosis|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-15-107', '24731071', 'Tuberculosis is an infectious bacterial disease caused by Mycobacterium tuberculosis. It remains a major health threat, killing over one million people every year worldwide. An early antibiotic therapy is the basis of the treatment, and the emergence and spread of multidrug and extensively drug-resistant mutant strains raise significant challenges. As these bacteria grow very slowly, drug resistance mutations are currently detected using molecular biology techniques. Resistance mutations are identified by sequencing the resistance-linked genes followed by a comparison with the literature data. The only online database is the TB Drug Resistance Mutation database (TBDReaM database), however, it requires mutation detection before use, and its interrogation is complex due to its loose syntax and grammar.'),
(96076, 2014, 'bmc', 'A two-step hierarchical hypothesis set testing framework, with applications to gene expression data on ordered categories', 'Li, Yihan|Ghosh, Debashis', 'Laboratoire de Biométrie et Biologie Évolutive, UMR CNRS 5558, Université Claude Bernard - Lyon 1, 43 bd, du 11 Novembre 1918, 69622 Villeurbanne Cedex, France. jp.flandrois@univ-lyon1.fr.|Department of Statistics, Pennsylvania State University, University Park, State College, Pennsylvania 16802, USA. ghoshd@psu.edu.', 'France|United States', 4, 'Breast Neoplasms|Estradiol|Gene Expression|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-15-108', '24731138', 'In complex large-scale experiments, in addition to simultaneously considering a large number of features, multiple hypotheses are often being tested for each feature. This leads to a problem of multi-dimensional multiple testing. For example, in gene expression studies over ordered categories (such as time-course or dose-response experiments), interest is often in testing differential expression across several categories for each gene. In this paper, we consider a framework for testing multiple sets of hypothesis, which can be applied to a wide range of problems.'),
(96077, 2014, 'bmc', 'Copy number variation detection using next generation sequencing read counts', 'Wang, Heng|Nettleton, Dan|Ying, Kai', 'Lyman Briggs College, Michigan State University, East Lansing, USA. hengwang@msu.edu.|Lyman Briggs College, Michigan State University, East Lansing, USA. hengwang@msu.edu.|Lyman Briggs College, Michigan State University, East Lansing, USA. hengwang@msu.edu.', 'United States|United States|United States', 49, 'Algorithms|Chromosomes, Plant|DNA Copy Number Variations|Genome, Plant|Genomics|High-Throughput Nucleotide Sequencing|Humans|Markov Chains|Sequence Analysis, DNA|Zea mays', 'Journal Article', '10.1186/1471-2105-15-109', '24731174', 'A copy number variation (CNV) is a difference between genotypes in the number of copies of a genomic region. Next generation sequencing (NGS) technologies provide sensitive and accurate tools for detecting genomic variations that include CNVs. However, statistical approaches for CNV identification using NGS are limited. We propose a new methodology for detecting CNVs using NGS data. This method (henceforth denoted by m-HMM) is based on a hidden Markov model with emission probabilities that are governed by mixture distributions. We use the Expectation-Maximization (EM) algorithm to estimate the parameters in the model.'),
(96078, 2014, 'bmc', 'On finding bicliques in bipartite graphs: a novel algorithm and its application to the integration of diverse biological data types', 'Zhang, Yun|Phillips, Charles A|Rogers, Gary L|Baker, Erich J|Chesler, Elissa J|Langston, Michael A', 'Lyman Briggs College, Michigan State University, East Lansing, USA. hengwang@msu.edu.|Lyman Briggs College, Michigan State University, East Lansing, USA. hengwang@msu.edu.|Lyman Briggs College, Michigan State University, East Lansing, USA. hengwang@msu.edu.|Lyman Briggs College, Michigan State University, East Lansing, USA. hengwang@msu.edu.|Lyman Briggs College, Michigan State University, East Lansing, USA. hengwang@msu.edu.|Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA. langston@eecs.utk.edu.', 'United States|United States|United States|United States|United States|United States', 49, 'Algorithms|Animals|Computer Graphics|Genomics|Humans|Mice|Rats|Software', 'Journal Article', '10.1186/1471-2105-15-110', '24731198', 'Integrating and analyzing heterogeneous genome-scale data is a huge algorithmic challenge for modern systems biology. Bipartite graphs can be useful for representing relationships across pairs of disparate data types, with the interpretation of these relationships accomplished through an enumeration of maximal bicliques. Most previously-known techniques are generally ill-suited to this foundational task, because they are relatively inefficient and without effective scaling. In this paper, a powerful new algorithm is described that produces all maximal bicliques in a bipartite graph. Unlike most previous approaches, the new method neither places undue restrictions on its input nor inflates the problem size. Efficiency is achieved through an innovative exploitation of bipartite graph structure, and through computational reductions that rapidly eliminate non-maximal candidates from the search space. An iterative selection of vertices for consideration based on non-decreasing common neighborhood sizes boosts efficiency and leads to more balanced recursion trees.'),
(96079, 2014, 'bmc', 'A comprehensive study of small non-frameshift insertions/deletions in proteins and prediction of their phenotypic effects by a machine learning method (KD4i)', 'Bermejo-Das-Neves, Carlos|Nguyen, Hoan-Ngoc|Poch, Olivier|Thompson, Julie D', 'Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA. langston@eecs.utk.edu.|Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA. langston@eecs.utk.edu.|Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA. langston@eecs.utk.edu.|ICube Laboratory and Strasbourg Federation of Translational Medicine (FMTS), University of Strasbourg and CNRS, Strasbourg, France. thompson@unistra.fr.', 'United States|United States|United States|France', 12, 'Artificial Intelligence|Humans|INDEL Mutation|Kinesin|Phenotype|Proteins', 'Journal Article', '10.1186/1471-2105-15-111', '24742296', 'Small insertion and deletion polymorphisms (Indels) are the second most common mutations in the human genome, after Single Nucleotide Polymorphisms (SNPs). Recent studies have shown that they have significant influence on genetic variation by altering human traits and can cause multiple human diseases. In particular, many Indels that occur in protein coding regions are known to impact the structure or function of the protein. A major challenge is to predict the effects of these Indels and to distinguish between deleterious and neutral variants. When an Indel occurs within a coding region, it can be either frameshifting (FS) or non-frameshifting (NFS). FS-Indels either modify the complete C-terminal region of the protein or result in premature termination of translation. NFS-Indels insert/delete multiples of three nucleotides leading to the insertion/deletion of one or more amino acids.'),
(96080, 2014, 'bmc', 'Structural genomics analysis of uncharacterized protein families overrepresented in human gut bacteria identifies a novel glycoside hydrolase', 'Sheydina, Anna|Eberhardt, Ruth Y|Rigden, Daniel J|Chang, Yuanyuan|Li, Zhanwen|Zmasek, Christian C|Axelrod, Herbert L|Godzik, Adam', 'ICube Laboratory and Strasbourg Federation of Translational Medicine (FMTS), University of Strasbourg and CNRS, Strasbourg, France. thompson@unistra.fr.|ICube Laboratory and Strasbourg Federation of Translational Medicine (FMTS), University of Strasbourg and CNRS, Strasbourg, France. thompson@unistra.fr.|ICube Laboratory and Strasbourg Federation of Translational Medicine (FMTS), University of Strasbourg and CNRS, Strasbourg, France. thompson@unistra.fr.|ICube Laboratory and Strasbourg Federation of Translational Medicine (FMTS), University of Strasbourg and CNRS, Strasbourg, France. thompson@unistra.fr.|ICube Laboratory and Strasbourg Federation of Translational Medicine (FMTS), University of Strasbourg and CNRS, Strasbourg, France. thompson@unistra.fr.|ICube Laboratory and Strasbourg Federation of Translational Medicine (FMTS), University of Strasbourg and CNRS, Strasbourg, France. thompson@unistra.fr.|ICube Laboratory and Strasbourg Federation of Translational Medicine (FMTS), University of Strasbourg and CNRS, Strasbourg, France. thompson@unistra.fr.|Joint Center for Structural Genomics, 10550 North Torrey Pines Road, BCC-206, La Jolla, California 92037, USA. adam@sanfordburnham.org.', 'France|France|France|France|France|France|France|United States', 9, 'Amino Acid Sequence|Bacterial Proteins|Bacteroides|Computational Biology|Gastrointestinal Tract|Genomics|Glycoside Hydrolases|Humans|Protein Structure, Tertiary', 'Journal Article', '10.1186/1471-2105-15-112', '24742328', 'Bacteroides spp. form a significant part of our gut microbiome and are well known for optimized metabolism of diverse polysaccharides. Initial analysis of the archetypal Bacteroides thetaiotaomicron genome identified 172 glycosyl hydrolases and a large number of uncharacterized proteins associated with polysaccharide metabolism.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96081, 2014, 'bmc', 'Probabilistic drug connectivity mapping', 'Parkkinen, Juuso A|Kaski, Samuel', 'Joint Center for Structural Genomics, 10550 North Torrey Pines Road, BCC-206, La Jolla, California 92037, USA. adam@sanfordburnham.org.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Espoo, Finland. samuel.kaski@aalto.fi.', 'United States|Finland', 18, 'Cell Line|Drug Evaluation, Preclinical|Gene Expression Profiling|Humans|Models, Statistical|Transcriptome', 'Journal Article', '10.1186/1471-2105-15-113', '24742351', 'The aim of connectivity mapping is to match drugs using drug-treatment gene expression profiles from multiple cell lines. This can be viewed as an information retrieval task, with the goal of finding the most relevant profiles for a given query drug. We infer the relevance for retrieval by data-driven probabilistic modeling of the drug responses, resulting in probabilistic connectivity mapping, and further consider the available cell lines as different data sources. We use a special type of probabilistic model to separate what is shared and specific between the sources, in contrast to earlier connectivity mapping methods that have intentionally aggregated all available data, neglecting information about the differences between the cell lines.'),
(96082, 2014, 'bmc', 'Biological relevance of CNV calling methods using familial relatedness including monozygotic twins', 'Castellani, Christina A|Melka, Melkaye G|Wishart, Andrea E|Locke, M Elizabeth O|Awamleh, Zain|OReilly, Richard L|Singh, Shiva M', 'Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Espoo, Finland. samuel.kaski@aalto.fi.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Espoo, Finland. samuel.kaski@aalto.fi.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Espoo, Finland. samuel.kaski@aalto.fi.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Espoo, Finland. samuel.kaski@aalto.fi.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Espoo, Finland. samuel.kaski@aalto.fi.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Espoo, Finland. samuel.kaski@aalto.fi.|Department of Biology, The University of Western Ontario, London N6A 5B7, ON, Canada. ssingh@uwo.ca.', 'Finland|Finland|Finland|Finland|Finland|Finland|Canada', 11, 'Algorithms|Chromosomes, Human|DNA Copy Number Variations|Genome, Human|Genome-Wide Association Study|Genomics|Genotype|Humans|Polymorphism, Single Nucleotide|Reproducibility of Results|Software|Twins, Monozygotic', 'Journal Article', '10.1186/1471-2105-15-114', '24750645', 'Studies involving the analysis of structural variation including Copy Number Variation (CNV) have recently exploded in the literature. Furthermore, CNVs have been associated with a number of complex diseases and neurodevelopmental disorders. Common methods for CNV detection use SNP, CNV, or CGH arrays, where the signal intensities of consecutive probes are used to define the number of copies associated with a given genomic region. These practices pose a number of challenges that interfere with the ability of available methods to accurately call CNVs. It has, therefore, become necessary to develop experimental protocols to test the reliability of CNV calling methods from microarray data so that researchers can properly discriminate biologically relevant data from noise.'),
(96083, 2014, 'bmc', 'Identifying pathogenic processes by integrating microarray data with prior knowledge', 'Nygård, Ståle|Reitan, Trond|Clancy, Trevor|Nygaard, Vegard|Bjørnstad, Johannes|Skrbic, Biljana|Tønnessen, Theis|Christensen, Geir|Hovig, Eivind', 'Bioinformatics Core Facility, Institute for Medical Informatics, Oslo University Hospital, Oslo, Norway. staaln@ifi.uio.no.|Bioinformatics Core Facility, Institute for Medical Informatics, Oslo University Hospital, Oslo, Norway. staaln@ifi.uio.no.|Bioinformatics Core Facility, Institute for Medical Informatics, Oslo University Hospital, Oslo, Norway. staaln@ifi.uio.no.|Bioinformatics Core Facility, Institute for Medical Informatics, Oslo University Hospital, Oslo, Norway. staaln@ifi.uio.no.|Bioinformatics Core Facility, Institute for Medical Informatics, Oslo University Hospital, Oslo, Norway. staaln@ifi.uio.no.|Bioinformatics Core Facility, Institute for Medical Informatics, Oslo University Hospital, Oslo, Norway. staaln@ifi.uio.no.|Bioinformatics Core Facility, Institute for Medical Informatics, Oslo University Hospital, Oslo, Norway. staaln@ifi.uio.no.|Bioinformatics Core Facility, Institute for Medical Informatics, Oslo University Hospital, Oslo, Norway. staaln@ifi.uio.no.|Bioinformatics Core Facility, Institute for Medical Informatics, Oslo University Hospital, Oslo, Norway. staaln@ifi.uio.no.', 'Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway', 2, 'Algorithms|Animals|Bayes Theorem|Cluster Analysis|Gene Expression Profiling|Gene Regulatory Networks|Heart Failure|Humans|Markov Chains|Melanoma|Mice|Monte Carlo Method|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Sequence Homology, Amino Acid|Transcription Factors', 'Journal Article', '10.1186/1471-2105-15-115', '24758699', 'It is of great importance to identify molecular processes and pathways that are involved in disease etiology. Although there has been an extensive use of various high-throughput methods for this task, pathogenic pathways are still not completely understood. Often the set of genes or proteins identified as altered in genome-wide screens show a poor overlap with canonical disease pathways. These findings are difficult to interpret, yet crucial in order to improve the understanding of the molecular processes underlying the disease progression. We present a novel method for identifying groups of connected molecules from a set of differentially expressed genes. These groups represent functional modules sharing common cellular function and involve signaling and regulatory events. Specifically, our method makes use of Bayesian statistics to identify groups of co-regulated genes based on the microarray data, where external information about molecular interactions and connections are used as priors in the group assignments. Markov chain Monte Carlo sampling is used to search for the most reliable grouping.'),
(96084, 2014, 'bmc', 'ShrinkBayes: a versatile R-package for analysis of count-based sequencing data in complex study designs', 'van de Wiel, Mark A|Neerincx, Maarten|Buffart, Tineke E|Sie, Daoud|Verheul, Henk M W', 'Department of Epidemiology and Biostatistics, VU University medical center, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands. mark.vdwiel@vumc.nl.|Department of Epidemiology and Biostatistics, VU University medical center, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands. mark.vdwiel@vumc.nl.|Department of Epidemiology and Biostatistics, VU University medical center, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands. mark.vdwiel@vumc.nl.|Department of Epidemiology and Biostatistics, VU University medical center, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands. mark.vdwiel@vumc.nl.|Department of Epidemiology and Biostatistics, VU University medical center, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands. mark.vdwiel@vumc.nl.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Bayes Theorem|Colonic Neoplasms|Humans|MicroRNAs|Sample Size|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-15-116', '24766777', 'Complex designs are common in (observational) clinical studies. Sequencing data for such studies are produced more and more often, implying challenges for the analysis, such as excess of zeros, presence of random effects and multi-parameter inference. Moreover, when sample sizes are small, inference is likely to be too liberal when, in a Bayesian setting, applying a non-appropriate prior or to lack power when not carefully borrowing information across features.'),
(96085, 2014, 'bmc', 'Scientists sense making when hypothesizing about disease mechanisms from expression data and their needs for visualization support', 'Mirel, Barbara|Görg, Carsten', 'School of Education, University of Michigan, Ann Arbor, Michigan 48109, USA. bmirel@umich.edu.|School of Education, University of Michigan, Ann Arbor, Michigan 48109, USA. bmirel@umich.edu.', 'United States|United States', 4, 'Disease|Gene Expression Profiling|Humans|Research Design', 'Editorial', '10.1186/1471-2105-15-117', '24766796', 'A common class of biomedical analysis is to explore expression data from high throughput experiments for the purpose of uncovering functional relationships that can lead to a hypothesis about mechanisms of a disease. We call this analysis expression driven, -omics hypothesizing. In it, scientists use interactive data visualizations and read deeply in the research literature. Little is known, however, about the actual flow of reasoning and behaviors (sense making) that scientists enact in this analysis, end-to-end. Understanding this flow is important because if bioinformatics tools are to be truly useful they must support it. Sense making models of visual analytics in other domains have been developed and used to inform the design of useful and usable tools. We believe they would be helpful in bioinformatics. To characterize the sense making involved in expression-driven, -omics hypothesizing, we conducted an in-depth observational study of one scientist as she engaged in this analysis over six months. From findings, we abstracted a preliminary sense making model. Here we describe its stages and suggest guidelines for developing visualization tools that we derived from this case. A single case cannot be generalized. But we offer our findings, sense making model and case-based tool guidelines as a first step toward increasing interest and further research in the bioinformatics field on scientists analytical workflows and their implications for tool design. '),
(96086, 2014, 'bmc', 'H2rs: deducing evolutionary and functionally important residue positions by means of an entropy and similarity based analysis of multiple sequence alignments', 'Janda, Jan-Oliver|Popal, Ajmal|Bauer, Jochen|Busch, Markus|Klocke, Michael|Spitzer, Wolfgang|Keller, Jörg|Merkl, Rainer', 'School of Education, University of Michigan, Ann Arbor, Michigan 48109, USA. bmirel@umich.edu.|School of Education, University of Michigan, Ann Arbor, Michigan 48109, USA. bmirel@umich.edu.|School of Education, University of Michigan, Ann Arbor, Michigan 48109, USA. bmirel@umich.edu.|School of Education, University of Michigan, Ann Arbor, Michigan 48109, USA. bmirel@umich.edu.|School of Education, University of Michigan, Ann Arbor, Michigan 48109, USA. bmirel@umich.edu.|School of Education, University of Michigan, Ann Arbor, Michigan 48109, USA. bmirel@umich.edu.|School of Education, University of Michigan, Ann Arbor, Michigan 48109, USA. bmirel@umich.edu.|Institute of Biophysics and Physical Biochemistry, University of Regensburg, D-93040 Regensburg, Germany. rainer.merkl@ur.de.', 'United States|United States|United States|United States|United States|United States|United States|Germany', 6, 'Algorithms|Amino Acids|Computer Simulation|Enzymes|Evolution, Molecular|Mutation|Protein Conformation|Proteins|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-15-118', '24766829', 'The identification of functionally important residue positions is an important task of computational biology. Methods of correlation analysis allow for the identification of pairs of residue positions, whose occupancy is mutually dependent due to constraints imposed by protein structure or function. A common measure assessing these dependencies is the mutual information, which is based on Shannons information theory that utilizes probabilities only. Consequently, such approaches do not consider the similarity of residue pairs, which may degrade the algorithms performance. One typical algorithm is H2r, which characterizes each individual residue position k by the conn(k)-value, which is the number of significantly correlated pairs it belongs to.'),
(96087, 2014, 'bmc', 'ConSole: using modularity of contact maps to locate solenoid domains in protein structures', 'Hrabe, Thomas|Godzik, Adam', 'Institute of Biophysics and Physical Biochemistry, University of Regensburg, D-93040 Regensburg, Germany. rainer.merkl@ur.de.|Program in Bioinformatics and Systems Biology, Sanford-Burnham Medical Research Institute, 92037 La Jolla, CA, USA. adam@godziklab.org.', 'Germany|United States', 0, 'Algorithms|Protein Conformation|Protein Structure, Tertiary|Proteins|Repetitive Sequences, Amino Acid|Software', 'Journal Article', '10.1186/1471-2105-15-119', '24766872', 'Periodic proteins, characterized by the presence of multiple repeats of short motifs, form an interesting and seldom-studied group. Due to often extreme divergence in sequence, detection and analysis of such motifs is performed more reliably on the structural level. Yet, few algorithms have been developed for the detection and analysis of structures of periodic proteins.'),
(96088, 2014, 'bmc', 'Accelerating the scoring module of mass spectrometry-based peptide identification using GPUs', 'Li, You|Chi, Hao|Xia, Leihao|Chu, Xiaowen', 'Program in Bioinformatics and Systems Biology, Sanford-Burnham Medical Research Institute, 92037 La Jolla, CA, USA. adam@godziklab.org.|Program in Bioinformatics and Systems Biology, Sanford-Burnham Medical Research Institute, 92037 La Jolla, CA, USA. adam@godziklab.org.|Program in Bioinformatics and Systems Biology, Sanford-Burnham Medical Research Institute, 92037 La Jolla, CA, USA. adam@godziklab.org.|Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong. chxw@comp.hkbu.edu.hk.', 'United States|United States|United States|Hong Kong', 9, 'Algorithms|Databases, Protein|Peptides|Proteins|Proteomics|Search Engine|Sequence Analysis, Protein|Software|Tandem Mass Spectrometry', 'Journal Article', '10.1186/1471-2105-15-121', '24773593', 'Tandem mass spectrometry-based database searching is currently the main method for protein identification in shotgun proteomics. The explosive growth of protein and peptide databases, which is a result of genome translations, enzymatic digestions, and post-translational modifications (PTMs), is making computational efficiency in database searching a serious challenge. Profile analysis shows that most search engines spend 50%-90% of their total time on the scoring module, and that the spectrum dot product (SDP) based scoring module is the most widely used. As a general purpose and high performance parallel hardware, graphics processing units (GPUs) are promising platforms for speeding up database searches in the protein identification process.'),
(96089, 2014, 'bmc', 'SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines', 'Cao, Renzhi|Wang, Zheng|Wang, Yiheng|Cheng, Jianlin', 'Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong. chxw@comp.hkbu.edu.hk.|Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong. chxw@comp.hkbu.edu.hk.|Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong. chxw@comp.hkbu.edu.hk.|Department of Computer Science, Informatics Institute, Christopher S, Bond Life Science Center, University of Missouri, Columbia, MO 65211, USA. chengji@missouri.edu.', 'Hong Kong|Hong Kong|Hong Kong|United States', 0, 'Amino Acids|Artificial Intelligence|Models, Molecular|Protein Conformation|Protein Structure, Secondary|Proteins|Sequence Analysis, Protein|Software|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-15-120', '24776231', 'It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models.'),
(96090, 2014, 'bmc', 'Transcript mapping based on dRNA-seq data', 'Bischler, Thorsten|Kopf, Matthias|Voß, Björn', 'Department of Computer Science, Informatics Institute, Christopher S, Bond Life Science Center, University of Missouri, Columbia, MO 65211, USA. chengji@missouri.edu.|Department of Computer Science, Informatics Institute, Christopher S, Bond Life Science Center, University of Missouri, Columbia, MO 65211, USA. chengji@missouri.edu.|Genetics & Experimental Bioinformatics, Institute for Biology 3, Faculty of Biology, Albert-Ludwigs-University Freiburg, Schänzlestr, 1, 79104 Freiburg, Germany. bjoern.voss@biologie.uni-freiburg.de.', 'United States|United States|Germany', 0, 'Algorithms|Gene Expression Profiling|Genomics|Helicobacter pylori|Operon|Sequence Analysis, RNA|Transcription Initiation Site|Untranslated Regions', 'Journal Article', '10.1186/1471-2105-15-122', '24780064', 'RNA-seq and its variant differential RNA-seq (dRNA-seq) are today routine methods for transcriptome analysis in bacteria. While expression profiling and transcriptional start site prediction are standard tasks today, the problem of identifying transcriptional units in a genome-wide fashion is still not solved for prokaryotic systems.'),
(96091, 2014, 'bmc', 'Protein-specific prediction of mRNA binding using RNA sequences, binding motifs and predicted secondary structures', 'Livi, Carmen M|Blanzieri, Enrico', 'Department of Information Engineering and Computer Science, University of Trento, Via Sommarive 5, Trento, Italy. carmenmaria.livi@crg.eu.|Department of Information Engineering and Computer Science, University of Trento, Via Sommarive 5, Trento, Italy. carmenmaria.livi@crg.eu.', 'Italy|Italy', 25, 'Computer Simulation|Humans|Nucleic Acid Conformation|RNA, Messenger|RNA-Binding Proteins|Sequence Analysis, RNA|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-15-123', '24780077', 'RNA-binding proteins interact with specific RNA molecules to regulate important cellular processes. It is therefore necessary to identify the RNA interaction partners in order to understand the precise functions of such proteins. Protein-RNA interactions are typically characterized using in vivo and in vitro experiments but these may not detect all binding partners. Therefore, computational methods that capture the protein-dependent nature of such binding interactions could help to predict potential binding partners in silico.'),
(96092, 2013, 'bmc', 'Proceedings of the Second IEEE International Conference on Computational Advances in Bio and Medical Sciences (ICCABS 2012): Bioinformatics, February 23-25, 2012, Las Vegas, Nevada', '-', '-', '-', 0, 'Computational Biology', 'Congress', '10.1186/1471-2105-15-123', '24795967', '-'),
(96093, 2013, 'bmc', 'Proceedings of The Second Workshop on Data Mining of Next-Generation Sequencing in conjunction with the 2012 IEEE International Conference on Bioinformatics and Biomedicine, October 4-7, 2012, Philadelphia, PA', '-', '-', '-', 0, 'Computational Biology', 'Congress', '10.1186/1471-2105-15-123', '24795968', '-'),
(96094, 2014, 'bmc', 'A predictor for predicting Escherichia coli transcriptome and the effects of gene perturbations', 'Ling, Maurice H T|Poh, Chueh Loo', 'School of Chemical and Biomedical Engineering, Nanyang Technological University, Nanyang Ave, Singapore, Singapore. mauriceling@acm.org.|School of Chemical and Biomedical Engineering, Nanyang Technological University, Nanyang Ave, Singapore, Singapore. mauriceling@acm.org.', 'Singapore|Singapore', 4, 'Endopeptidases|Escherichia coli|Gene Expression Profiling|Gene Expression Regulation, Bacterial|Gene Knockout Techniques|Gene Regulatory Networks|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-15-140', '24884349', 'A means to predict the effects of gene over-expression, knockouts, and environmental stimuli in silico is useful for system biologists to develop and test hypotheses. Several studies had predicted the expression of all Escherichia coli genes from sequences and reported a correlation of 0.301 between predicted and actual expression. However, these do not allow biologists to study the effects of gene perturbations on the native transcriptome.'),
(96095, 2014, 'bmc', 'A resource-saving collective approach to biomedical semantic role labeling', 'Tsai, Richard Tzong-Han|Lai, Po-Ting', 'Department of Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan, Republic of China. thtsai@csie.ncu.edu.tw.|Department of Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan, Republic of China. thtsai@csie.ncu.edu.tw.', 'China|China', 2, 'Biomedical Research|Data Mining|Databases, Factual|Markov Chains|Semantics', 'Journal Article', '10.1186/1471-2105-15-160', '24884358', 'Biomedical semantic role labeling (BioSRL) is a natural language processing technique that identifies the semantic roles of the words or phrases in sentences describing biological processes and expresses them as predicate-argument structures (PASs). Currently, a major problem of BioSRL is that most systems label every node in a full parse tree independently, however, some nodes always exhibit dependency. In general SRL, collective approaches based on the Markov logic network (MLN) model have been successful in dealing with this problem. However, in BioSRL such an approach has not been attempted because it would require more training data to recognize the more specialized and diverse terms found in biomedical literature, increasing training time and computational complexity.'),
(96096, 2014, 'bmc', 'DMRforPairs: identifying differentially methylated regions between unique samples using array based methylation profiles', 'Rijlaarsdam, Martin A|van der Zwan, Yvonne G|Dorssers, Lambert C J|Looijenga, Leendert H J', 'Department of Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan, Republic of China. thtsai@csie.ncu.edu.tw.|Department of Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan, Republic of China. thtsai@csie.ncu.edu.tw.|Department of Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan, Republic of China. thtsai@csie.ncu.edu.tw.|Department of Pathology, Laboratory for Experimental Patho-Oncology, Erasmus MC - University Medical Center Rotterdam, Be-432, P,O, Box 2040, Rotterdam 3000 CA, Netherlands. l.looijenga@erasmusmc.nl.', 'China|China|China|Netherlands', 9, 'Cell Line|Cell Line, Tumor|DNA Methylation|Female|Genomics|Humans|MCF-7 Cells|Male|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-15-141', '24884391', 'Array based methylation profiling is a cost-effective solution to study the association between genome methylation and human disease & development. Available tools to analyze the Illumina Infinium HumanMethylation450 BeadChip focus on comparing methylation levels per locus. Other tools combine multiple probes into a range, identifying differential methylated regions (DMRs). These tools all require groups of samples to compare. However, comparison of unique, individual samples is essential in situations where larger sample sizes are not possible.'),
(96097, 2014, 'bmc', 'A highly conserved WDYPKCDRA epitope in the RNA directed RNA polymerase of human coronaviruses can be used as epitope-based universal vaccine design', 'Sharmin, Refat|Islam, Abul Bashar Mir Md Khademul', 'Department of Pathology, Laboratory for Experimental Patho-Oncology, Erasmus MC - University Medical Center Rotterdam, Be-432, P,O, Box 2040, Rotterdam 3000 CA, Netherlands. l.looijenga@erasmusmc.nl.|Department of Genetic Engineering and Biotechnology, University of Dhaka, Science Complex Building, Dhaka 1000, Bangladesh. khademul@du.ac.bd.', 'Netherlands|Bangladesh', 0, 'Algorithms|Amino Acid Sequence|Conserved Sequence|Coronavirus|Epitopes|Humans|RNA Replicase|Sequence Alignment|Viral Proteins|Viral Vaccines', 'Journal Article', '10.1186/1471-2105-15-161', '24884408', 'Coronaviruses are the diverse group of RNA virus. From 1960, six strains of human coronaviruses have emerged that includes SARS-CoV and the recent infection by deadly MERS-CoV which is now going to cause another outbreak. Prevention of these viruses is urgent and a universal vaccine for all strain could be a promising solution in this circumstance. In this study we aimed to design an epitope based vaccine against all strain of human coronavirus.'),
(96098, 2014, 'bmc', 'Detecting differentially methylated loci for multiple treatments based on high-throughput methylation data', 'Chen, Zhongxue|Huang, Hanwen|Liu, Qingzhong', 'Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, 1025 E, 7th street, PH C104, Bloomington, IN 47405, USA. zc3@indiana.edu.|Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, 1025 E, 7th street, PH C104, Bloomington, IN 47405, USA. zc3@indiana.edu.|Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, 1025 E, 7th street, PH C104, Bloomington, IN 47405, USA. zc3@indiana.edu.', 'India|India|India', 5, 'Case-Control Studies|DNA Methylation|Female|Genetic Loci|Humans|Oligonucleotide Array Sequence Analysis|Ovarian Neoplasms|Statistics, Nonparametric', 'Journal Article', '10.1186/1471-2105-15-142', '24884464', 'Because of its important effects, as an epigenetic factor, on gene expression and disease development, DNA methylation has drawn much attention from researchers. Detecting differentially methylated loci is an important but challenging step in studying the regulatory roles of DNA methylation in a broad range of biological processes and diseases. Several statistical approaches have been proposed to detect significant methylated loci, however, most of them were designed specifically for case-control studies.'),
(96099, 2014, 'bmc', 'A multivariate approach to the integration of multi-omics datasets', 'Meng, Chen|Kuster, Bernhard|Culhane, Aedín C|Gholami, Amin Moghaddas', 'Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, 1025 E, 7th street, PH C104, Bloomington, IN 47405, USA. zc3@indiana.edu.|Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, 1025 E, 7th street, PH C104, Bloomington, IN 47405, USA. zc3@indiana.edu.|Chair of Proteomics and Bioanalytics, Technische Universität München, Freising, Germany. aedin@jimmy.harvard.edu.|Chair of Proteomics and Bioanalytics, Technische Universität München, Freising, Germany. aedin@jimmy.harvard.edu.', 'India|India|Germany|Germany', 97, 'Biomarkers, Tumor|Cell Line, Tumor|Female|Genomics|High-Throughput Nucleotide Sequencing|Humans|Ovarian Neoplasms|Proteome', 'Journal Article', '10.1186/1471-2105-15-162', '24884486', 'To leverage the potential of multi-omics studies, exploratory data analysis methods that provide systematic integration and comparison of multiple layers of omics information are required. We describe multiple co-inertia analysis (MCIA), an exploratory data analysis method that identifies co-relationships between multiple high dimensional datasets. Based on a covariance optimization criterion, MCIA simultaneously projects several datasets into the same dimensional space, transforming diverse sets of features onto the same scale, to extract the most variant from each dataset and facilitate biological interpretation and pathway analysis.'),
(96100, 2014, 'bmc', 'Efficient discovery of responses of proteins to compounds using active learning', 'Kangas, Joshua D|Naik, Armaghan W|Murphy, Robert F', 'Chair of Proteomics and Bioanalytics, Technische Universität München, Freising, Germany. aedin@jimmy.harvard.edu.|Chair of Proteomics and Bioanalytics, Technische Universität München, Freising, Germany. aedin@jimmy.harvard.edu.|Lane Center for Computational Biology, Carnegie Mellon University, 5000 Forbes Ave,, Pittsburgh, PA 15213, USA. murphy@cmu.edu.', 'Germany|Germany|United States', 0, 'Algorithms|Artificial Intelligence|Drug Discovery|Humans|Proteins', 'Journal Article', '10.1186/1471-2105-15-143', '24884564', 'Drug discovery and development has been aided by high throughput screening methods that detect compound effects on a single target. However, when using focused initial screening, undesirable secondary effects are often detected late in the development process after significant investment has been made. An alternative approach would be to screen against undesired effects early in the process, but the number of possible secondary targets makes this prohibitively expensive.'),
(96101, 2014, 'bmc', 'Population genetic analysis of bi-allelic structural variants from low-coverage sequence data with an expectation-maximization algorithm', 'Lucas-Lledó, José Ignacio|Vicente-Salvador, David|Aguado, Cristina|Cáceres, Mario', 'Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, 08193 Bellaterra (Barcelona), Spain. lucas.lledo@igb-berlin.de.|Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, 08193 Bellaterra (Barcelona), Spain. lucas.lledo@igb-berlin.de.|Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, 08193 Bellaterra (Barcelona), Spain. lucas.lledo@igb-berlin.de.|Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, 08193 Bellaterra (Barcelona), Spain. lucas.lledo@igb-berlin.de.', 'Spain|Spain|Spain|Spain', 0, 'Algorithms|Alleles|Genetics, Population|Genome|Genomics|Genotype|High-Throughput Nucleotide Sequencing|Humans|Likelihood Functions|Polymorphism, Genetic', 'Journal Article', '10.1186/1471-2105-15-163', '24884587', 'Population genetics and association studies usually rely on a set of known variable sites that are then genotyped in subsequent samples, because it is easier to genotype than to discover the variation. This is also true for structural variation detected from sequence data. However, the genotypes at known variable sites can only be inferred with uncertainty from low coverage data. Thus, statistical approaches that infer genotype likelihoods, test hypotheses, and estimate population parameters without requiring accurate genotypes are becoming popular. Unfortunately, the current implementations of these methods are intended to analyse only single nucleotide and short indel variation, and they usually assume that the two alleles in a heterozygous individual are sampled with equal probability. This is generally false for structural variants detected with paired ends or split reads. Therefore, the population genetics of structural variants cannot be studied, unless a painstaking and potentially biased genotyping is performed first.'),
(96102, 2014, 'bmc', 'The discriminant power of RNA features for pre-miRNA recognition', 'Lopes, Ivani de O N|Schliep, Alexander|de Carvalho, André C P de L F', 'Empresa Brasileira de Pesquisa Agropecuária, Embrapa Soja, Caixa Postal 231, Londrina-PR, CEP 86001-970, Brasil. ivani.negrao@embrapa.br.|Empresa Brasileira de Pesquisa Agropecuária, Embrapa Soja, Caixa Postal 231, Londrina-PR, CEP 86001-970, Brasil. ivani.negrao@embrapa.br.|Empresa Brasileira de Pesquisa Agropecuária, Embrapa Soja, Caixa Postal 231, Londrina-PR, CEP 86001-970, Brasil. ivani.negrao@embrapa.br.', '-|-|-', 25, 'Algorithms|Artificial Intelligence|Base Composition|Computational Biology|Humans|MicroRNAs|RNA Precursors|Software', 'Journal Article', '10.1186/1471-2105-15-124', '24884650', 'Computational discovery of microRNAs (miRNA) is based on pre-determined sets of features from miRNA precursors (pre-miRNA). Some feature sets are composed of sequence-structure patterns commonly found in pre-miRNAs, while others are a combination of more sophisticated RNA features. In this work, we analyze the discriminant power of seven feature sets, which are used in six pre-miRNA prediction tools. The analysis is based on the classification performance achieved with these feature sets for the training algorithms used in these tools. We also evaluate feature discrimination through the F-score and feature importance in the induction of random forests.'),
(96103, 2014, 'bmc', 'MOIRAI: a compact workflow system for CAGE analysis', 'Hasegawa, Akira|Daub, Carsten|Carninci, Piero|Hayashizaki, Yoshihide|Lassmann, Timo', 'Empresa Brasileira de Pesquisa Agropecuária, Embrapa Soja, Caixa Postal 231, Londrina-PR, CEP 86001-970, Brasil. ivani.negrao@embrapa.br.|Empresa Brasileira de Pesquisa Agropecuária, Embrapa Soja, Caixa Postal 231, Londrina-PR, CEP 86001-970, Brasil. ivani.negrao@embrapa.br.|Empresa Brasileira de Pesquisa Agropecuária, Embrapa Soja, Caixa Postal 231, Londrina-PR, CEP 86001-970, Brasil. ivani.negrao@embrapa.br.|Empresa Brasileira de Pesquisa Agropecuária, Embrapa Soja, Caixa Postal 231, Londrina-PR, CEP 86001-970, Brasil. ivani.negrao@embrapa.br.|RIKEN Center for Life Science Technologies (CLST), Riken Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045 Kanagawa, Japan. lassmann@gsc.riken.jp.', '-|-|-|-|Japan', 0, 'Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|K562 Cells|Molecular Sequence Annotation|Software|Workflow', 'Journal Article', '10.1186/1471-2105-15-144', '24884663', 'Cap analysis of gene expression (CAGE) is a sequencing based technology to capture the 5 ends of RNAs in a biological sample. After mapping, a CAGE peak on the genome indicates the position of an active transcriptional start site (TSS) and the number of reads correspond to its expression level. CAGE is prominently used in both the FANTOM and ENCODE project but presently there is no software package to perform the essential data processing steps.'),
(96104, 2014, 'bmc', 'WinHAP2: an extremely fast haplotype phasing program for long genotype sequences', 'Pan, Weihua|Zhao, Yanan|Xu, Yun|Zhou, Fengfeng', 'RIKEN Center for Life Science Technologies (CLST), Riken Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045 Kanagawa, Japan. lassmann@gsc.riken.jp.|RIKEN Center for Life Science Technologies (CLST), Riken Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045 Kanagawa, Japan. lassmann@gsc.riken.jp.|School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027, P,R, China. xuyun@ustc.edu.cn.|School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027, P,R, China. xuyun@ustc.edu.cn.', 'Japan|Japan|China|China', 5, 'Algorithms|Base Sequence|Genomics|Haplotypes|Humans|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1186/1471-2105-15-164', '24884701', 'The haplotype phasing problem tries to screen for phenotype associated genomic variations from millions of candidate data. Most of the current computer programs handle this problem with high requirements of computing power and memory. By replacing the computation-intensive step of constructing the maximum spanning tree with a heuristics of estimated initial haplotype, we released the WinHAP algorithm version 1.0, which outperforms the other algorithms in terms of both running speed and overall accuracy.'),
(96105, 2014, 'bmc', 'Effective filtering strategies to improve data quality from population-based whole exome sequencing studies', 'Carson, Andrew R|Smith, Erin N|Matsui, Hiroko|Brækkan, Sigrid K|Jepsen, Kristen|Hansen, John-Bjarne|Frazer, Kelly A', 'School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027, P,R, China. xuyun@ustc.edu.cn.|School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027, P,R, China. xuyun@ustc.edu.cn.|School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027, P,R, China. xuyun@ustc.edu.cn.|School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027, P,R, China. xuyun@ustc.edu.cn.|School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027, P,R, China. xuyun@ustc.edu.cn.|School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027, P,R, China. xuyun@ustc.edu.cn.|Department of Pediatrics and Rady Childrens Hospital, University of California San Diego, San Diego, USA. kafrazer@ucsd.edu.', 'China|China|China|China|China|China|United States', 55, 'Exome|Genotype|High-Throughput Nucleotide Sequencing|Humans|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-15-125', '24884706', 'Genotypes generated in next generation sequencing studies contain errors which can significantly impact the power to detect signals in common and rare variant association tests. These genotyping errors are not explicitly filtered by the standard GATK Variant Quality Score Recalibration (VQSR) tool and thus remain a source of errors in whole exome sequencing (WES) projects that follow GATKs recommended best practices. Therefore, additional data filtering methods are required to effectively remove these errors before performing association analyses with complex phenotypes. Here we empirically derive thresholds for genotype and variant filters that, when used in conjunction with the VQSR tool, achieve higher data quality than when using VQSR alone.'),
(96106, 2014, 'bmc', 'Transcriptome dynamics-based operon prediction in prokaryotes', 'Fortino, Vittorio|Smolander, Olli-Pekka|Auvinen, Petri|Tagliaferri, Roberto|Greco, Dario', 'Department of Computer Science (DI), NeuRoNe Lab, University of Salerno, via ponte don Melillo 84084, Fisciano, (SA), Italy. vittorio.fortino@ttl.fi.|Department of Computer Science (DI), NeuRoNe Lab, University of Salerno, via ponte don Melillo 84084, Fisciano, (SA), Italy. vittorio.fortino@ttl.fi.|Department of Computer Science (DI), NeuRoNe Lab, University of Salerno, via ponte don Melillo 84084, Fisciano, (SA), Italy. vittorio.fortino@ttl.fi.|Department of Computer Science (DI), NeuRoNe Lab, University of Salerno, via ponte don Melillo 84084, Fisciano, (SA), Italy. vittorio.fortino@ttl.fi.|Department of Computer Science (DI), NeuRoNe Lab, University of Salerno, via ponte don Melillo 84084, Fisciano, (SA), Italy. vittorio.fortino@ttl.fi.', 'Italy|Italy|Italy|Italy|Italy', 16, 'Gene Expression Profiling|Genome, Bacterial|Genomics|Molecular Sequence Annotation|Operon|Sequence Analysis, DNA|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-15-145', '24884724', 'Inferring operon maps is crucial to understanding the regulatory networks of prokaryotic genomes. Recently, RNA-seq based transcriptome studies revealed that in many bacterial species the operon structure vary with the change of environmental conditions. Therefore, new computational solutions that use both static and dynamic data are necessary to create condition specific operon predictions.'),
(96107, 2014, 'bmc', 'GO2MSIG, an automated GO based multi-species gene set generator for gene set enrichment analysis', 'Powell, Justin Andrew Christiaan', 'Takeda Cambridge Ltd, 418 Cambridge Science Park, Milton Road, Cambridge CB4 0PZ, UK. jpowell@takedacam.com.', 'United Kingdom', 16, 'Gene Expression Profiling|Gene Ontology|Genes|Humans|Internet|Software', 'Journal Article', '10.1186/1471-2105-15-146', '24884810', 'Despite the widespread use of high throughput expression platforms and the availability of a desktop implementation of Gene Set Enrichment Analysis (GSEA) that enables non-experts to perform gene set based analyses, the availability of the necessary precompiled gene sets is rare for species other than human.'),
(96108, 2014, 'bmc', 'Cache-Oblivious parallel SIMD Viterbi decoding for sequence search in HMMER', 'Ferreira, Miguel|Roma, Nuno|Russo, Luis M S', 'Takeda Cambridge Ltd, 418 Cambridge Science Park, Milton Road, Cambridge CB4 0PZ, UK. jpowell@takedacam.com.|Takeda Cambridge Ltd, 418 Cambridge Science Park, Milton Road, Cambridge CB4 0PZ, UK. jpowell@takedacam.com.|Instituto Superior Técnico, Universidade de Lisboa, Av, Rovisco Pais, 1049-001 Lisboa, Portugal. lsr@kdbio.inesc-id.pt.', 'United Kingdom|United Kingdom|Portugal', 5, 'Algorithms|Computational Biology|Databases, Genetic|Databases, Protein|Humans|Markov Chains|Sequence Alignment|Sequence Analysis', 'Journal Article', '10.1186/1471-2105-15-165', '24884826', 'HMMER is a commonly used bioinformatics tool based on Hidden Markov Models (HMMs) to analyze and process biological sequences. One of its main homology engines is based on the Viterbi decoding algorithm, which was already highly parallelized and optimized using Farrars striped processing pattern with Intel SSE2 instruction set extension.'),
(96109, 2014, 'bmc', 'Automated ensemble assembly and validation of microbial genomes', 'Koren, Sergey|Treangen, Todd J|Hill, Christopher M|Pop, Mihai|Phillippy, Adam M', 'National Biodefense Analysis and Countermeasures Center, 110 Thomas Johnson Drive, Frederick, MD 21702, USA. korens@nbacc.net.|National Biodefense Analysis and Countermeasures Center, 110 Thomas Johnson Drive, Frederick, MD 21702, USA. korens@nbacc.net.|National Biodefense Analysis and Countermeasures Center, 110 Thomas Johnson Drive, Frederick, MD 21702, USA. korens@nbacc.net.|National Biodefense Analysis and Countermeasures Center, 110 Thomas Johnson Drive, Frederick, MD 21702, USA. korens@nbacc.net.|National Biodefense Analysis and Countermeasures Center, 110 Thomas Johnson Drive, Frederick, MD 21702, USA. korens@nbacc.net.', 'United States|United States|United States|United States|United States', 37, 'Genome, Bacterial|Genome, Microbial|Genomics|Mycobacterium tuberculosis|Rhodobacter sphaeroides|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-15-126', '24884846', 'The continued democratization of DNA sequencing has sparked a new wave of development of genome assembly and assembly validation methods. As individual research labs, rather than centralized centers, begin to sequence the majority of new genomes, it is important to establish best practices for genome assembly. However, recent evaluations such as GAGE and the Assemblathon have concluded that there is no single best approach to genome assembly. Instead, it is preferable to generate multiple assemblies and validate them to determine which is most useful for the desired analysis, this is a labor-intensive process that is often impossible or unfeasible.'),
(96110, 2014, 'bmc', 'A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures', 'Jabbari, Hosna|Condon, Anne', 'Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver, Canada. hjabbari@cs.ubc.ca.|Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver, Canada. hjabbari@cs.ubc.ca.', 'Canada|Canada', 14, 'Algorithms|Base Sequence|High-Throughput Nucleotide Sequencing|Humans|Nucleic Acid Conformation|RNA|Sequence Analysis, RNA|Software|Time Factors', 'Journal Article', '10.1186/1471-2105-15-147', '24884954', 'Improving accuracy and efficiency of computational methods that predict pseudoknotted RNA secondary structures is an ongoing challenge. Existing methods based on free energy minimization tend to be very slow and are limited in the types of pseudoknots that they can predict. Incorporating known structural information can improve prediction accuracy, however, there are not many methods for prediction of pseudoknotted structures that can incorporate structural information as input. There is even less understanding of the relative robustness of these methods with respect to partial information.'),
(96111, 2014, 'bmc', 'A practical approximation algorithm for solving massive instances of hybridization number for binary and nonbinary trees', 'van Iersel, Leo|Kelk, Steven|Lekixc4x87, Nela|Scornavacca, Celine', 'Centrum Wiskunde & Informatica (CWI), P,O, Box 94079, 1090 GB, Amsterdam, The Netherlands. l.j.j.v.iersel@gmail.com.|Centrum Wiskunde & Informatica (CWI), P,O, Box 94079, 1090 GB, Amsterdam, The Netherlands. l.j.j.v.iersel@gmail.com.|Centrum Wiskunde & Informatica (CWI), P,O, Box 94079, 1090 GB, Amsterdam, The Netherlands. l.j.j.v.iersel@gmail.com.|Centrum Wiskunde & Informatica (CWI), P,O, Box 94079, 1090 GB, Amsterdam, The Netherlands. l.j.j.v.iersel@gmail.com.', 'Netherlands|Netherlands|Netherlands|Netherlands', 7, 'Algorithms|Hybridization, Genetic|Phylogeny|Software', 'Journal Article', '10.1186/1471-2105-15-127', '24884964', 'Reticulate events play an important role in determining evolutionary relationships. The problem of computing the minimum number of such events to explain discordance between two phylogenetic trees is a hard computational problem. Even for binary trees, exact solvers struggle to solve instances with reticulation number larger than 40-50.'),
(96112, 2014, 'bmc', 'Improvement of domain-level ortholog clustering by optimizing domain-specific sum-of-pairs score', 'Chiba, Hirokazu|Uchiyama, Ikuo', 'Centrum Wiskunde & Informatica (CWI), P,O, Box 94079, 1090 GB, Amsterdam, The Netherlands. l.j.j.v.iersel@gmail.com.|National Institute for Basic Biology, National Institutes of Natural Sciences, Nishigonaka 38, Myodaiji, Okazaki 444-8585, Japan. uchiyama@nibb.ac.jp.', 'Netherlands|Japan', 6, 'Cluster Analysis|Genomics|Phylogeny|Protein Structure, Tertiary|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-15-148', '24885064', 'Identification of ortholog groups is a crucial step in comparative analysis of multiple genomes. Although several computational methods have been developed to create ortholog groups, most of those methods do not evaluate orthology at the sub-gene level. In our method for domain-level ortholog clustering, DomClust, proteins are split into domains on the basis of alignment boundaries identified by all-against-all pairwise comparison, but it often fails to determine appropriate boundaries.'),
(96113, 2014, 'bmc', 'BLASTGrabber: a bioinformatic tool for visualization, analysis and sequence selection of massive BLAST data', 'Neumann, Ralf Stefan|Kumar, Surendra|Haverkamp, Thomas Hendricus Augustus|Shalchian-Tabrizi, Kamran', 'National Institute for Basic Biology, National Institutes of Natural Sciences, Nishigonaka 38, Myodaiji, Okazaki 444-8585, Japan. uchiyama@nibb.ac.jp.|National Institute for Basic Biology, National Institutes of Natural Sciences, Nishigonaka 38, Myodaiji, Okazaki 444-8585, Japan. uchiyama@nibb.ac.jp.|National Institute for Basic Biology, National Institutes of Natural Sciences, Nishigonaka 38, Myodaiji, Okazaki 444-8585, Japan. uchiyama@nibb.ac.jp.|Section for Genetics and Evolutionary Biology (EVOGENE) and Centre for Epigenetics, Development and Evolution (CEDE), University of Oslo, Oslo, Norway. kamran@ibv.uio.no.', 'Japan|Japan|Japan|Norway', 6, 'Algorithms|Amino Acid Sequence|Computational Biology|Computing Methodologies|Databases, Factual|High-Throughput Nucleotide Sequencing|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-15-128', '24885091', 'Advances in sequencing efficiency have vastly increased the sizes of biological sequence databases, including many thousands of genome-sequenced species. The BLAST algorithm remains the main search engine for retrieving sequence information, and must consequently handle data on an unprecedented scale. This has been possible due to high-performance computers and parallel processing. However, the raw BLAST output from contemporary searches involving thousands of queries becomes ill-suited for direct human processing. Few programs attempt to directly visualize and interpret BLAST output, those that do often provide a mere basic structuring of BLAST data.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96114, 2014, 'bmc', 'A web-based protein interaction network visualizer', 'Salazar, Gustavo A|Meintjes, Ayton|Mazandu, Gaston K|Rapanoël, Holifidy A|Akinola, Richard O|Mulder, Nicola J', 'Computational Biology Group, IDM, Faculty of Health Sciences, University of Cape Town, Anzio Road, Cape Town, South Africa. gustavo@cbio.uct.ac.za.|Computational Biology Group, IDM, Faculty of Health Sciences, University of Cape Town, Anzio Road, Cape Town, South Africa. gustavo@cbio.uct.ac.za.|Computational Biology Group, IDM, Faculty of Health Sciences, University of Cape Town, Anzio Road, Cape Town, South Africa. gustavo@cbio.uct.ac.za.|Computational Biology Group, IDM, Faculty of Health Sciences, University of Cape Town, Anzio Road, Cape Town, South Africa. gustavo@cbio.uct.ac.za.|Computational Biology Group, IDM, Faculty of Health Sciences, University of Cape Town, Anzio Road, Cape Town, South Africa. gustavo@cbio.uct.ac.za.|Computational Biology Group, IDM, Faculty of Health Sciences, University of Cape Town, Anzio Road, Cape Town, South Africa. gustavo@cbio.uct.ac.za.', 'South Africa|South Africa|South Africa|South Africa|South Africa|South Africa', 16, 'Computer Graphics|Humans|Internet|Protein Interaction Mapping|Protein Interaction Maps|Software', 'Journal Article', '10.1186/1471-2105-15-129', '24885165', 'Interaction between proteins is one of the most important mechanisms in the execution of cellular functions. The study of these interactions has provided insight into the functioning of an organisms processes. As of October 2013, Homo sapiens had over 170000 Protein-Protein interactions (PPI) registered in the Interologous Interaction Database, which is only one of the many public resources where protein interactions can be accessed. These numbers exemplify the volume of data that research on the topic has generated. Visualization of large data sets is a well known strategy to make sense of information, and protein interaction data is no exception. There are several tools that allow the exploration of this data, providing different methods to visualize protein network interactions. However, there is still no native web tool that allows this data to be explored interactively online.'),
(96115, 2014, 'bmc', 'FIGG: simulating populations of whole genome sequences for heterogeneous data analyses', 'Killcoyne, Sarah|del Sol, Antonio', 'Computational Biology Group, IDM, Faculty of Health Sciences, University of Cape Town, Anzio Road, Cape Town, South Africa. gustavo@cbio.uct.ac.za.|Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts fourneaux, Esch/Alzette L-4362, Luxembourg. antonio.delsol@uni.lu.', 'South Africa|Luxembourg', 4, 'Computer Simulation|Genetic Variation|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Mutation|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-15-149', '24885193', 'High-throughput sequencing has become one of the primary tools for investigation of the molecular basis of disease. The increasing use of sequencing in investigations that aim to understand both individuals and populations is challenging our ability to develop analysis tools that scale with the data. This issue is of particular concern in studies that exhibit a wide degree of heterogeneity or deviation from the standard reference genome. The advent of population scale sequencing studies requires analysis tools that are developed and tested against matching quantities of heterogeneous data.'),
(96116, 2014, 'bmc', 'BicSPAM: flexible biclustering using sequential patterns', 'Henriques, Rui|Madeira, Sara C', 'Knowledge Discovery and BIOInformatics group (KDBIO), INESC-ID, and Computer Science and Engineering (CSE) Department, Instituto Superior Técnico, Universidade de Lisboa, Av, Rovisco Pais, 1, 1049-001 Lisboa, Portugal. rmch@tecnico.ulisboa.pt.|Knowledge Discovery and BIOInformatics group (KDBIO), INESC-ID, and Computer Science and Engineering (CSE) Department, Instituto Superior Técnico, Universidade de Lisboa, Av, Rovisco Pais, 1, 1049-001 Lisboa, Portugal. rmch@tecnico.ulisboa.pt.', 'Portugal|Portugal', 23, 'Algorithms|Cluster Analysis|Data Mining|Gene Expression|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans', 'Journal Article', '10.1186/1471-2105-15-130', '24885271', 'Biclustering is a critical task for biomedical applications. Order-preserving biclusters, submatrices where the values of rows induce the same linear ordering across columns, capture local regularities with constant, shifting, scaling and sequential assumptions. Additionally, biclustering approaches relying on pattern mining output deliver exhaustive solutions with an arbitrary number and positioning of biclusters. However, existing order-preserving approaches suffer from robustness, scalability and/or flexibility issues. Additionally, they are not able to discover biclusters with symmetries and parameterizable levels of noise.'),
(96117, 2014, 'bmc', 'From sequence to enzyme mechanism using multi-label machine learning', 'De Ferrari, Luna|Mitchell, John B O', 'Biomedical Sciences Research Complex and EaStCHEM School of Chemistry, Purdie Building, University of St Andrews, North Haugh, St Andrews, Scotland KY16 9ST, UK. ldeferr@staffmail.ed.ac.uk.|Biomedical Sciences Research Complex and EaStCHEM School of Chemistry, Purdie Building, University of St Andrews, North Haugh, St Andrews, Scotland KY16 9ST, UK. ldeferr@staffmail.ed.ac.uk.', 'United Kingdom|United Kingdom', 13, 'Algorithms|Artificial Intelligence|Catalysis|Catalytic Domain|Databases, Protein|Enzymes|Protein Conformation|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-15-150', '24885296', 'In this work we predict enzyme function at the level of chemical mechanism, providing a finer granularity of annotation than traditional Enzyme Commission (EC) classes. Hence we can predict not only whether a putative enzyme in a newly sequenced organism has the potential to perform a certain reaction, but how the reaction is performed, using which cofactors and with susceptibility to which drugs or inhibitors, details with important consequences for drug and enzyme design. Work that predicts enzyme catalytic activity based on 3D protein structure features limits the prediction of mechanism to proteins already having either a solved structure or a close relative suitable for homology modelling.'),
(96118, 2014, 'bmc', 'HECTOR: a parallel multistage homopolymer spectrum based error corrector for 454 sequencing data', 'Wirawan, Adrianto|Harris, Robert S|Liu, Yongchao|Schmidt, Bertil|Schröder, Jan', 'Institut für Informatik, Johannes Gutenberg Universität Mainz, Mainz, Germany. wirawan@uni-mainz.de.|Institut für Informatik, Johannes Gutenberg Universität Mainz, Mainz, Germany. wirawan@uni-mainz.de.|Institut für Informatik, Johannes Gutenberg Universität Mainz, Mainz, Germany. wirawan@uni-mainz.de.|Institut für Informatik, Johannes Gutenberg Universität Mainz, Mainz, Germany. wirawan@uni-mainz.de.|Institut für Informatik, Johannes Gutenberg Universität Mainz, Mainz, Germany. wirawan@uni-mainz.de.', 'Germany|Germany|Germany|Germany|Germany', 21, 'Algorithms|High-Throughput Nucleotide Sequencing|Sequence Alignment|Software', 'Evaluation Studies', '10.1186/1471-2105-15-131', '24885381', 'Current-generation sequencing technologies are able to produce low-cost, high-throughput reads. However, the produced reads are imperfect and may contain various sequencing errors. Although many error correction methods have been developed in recent years, none explicitly targets homopolymer-length errors in the 454 sequencing reads.'),
(96119, 2014, 'bmc', 'A formal concept analysis approach to consensus clustering of multi-experiment expression data', 'Hristoskova, Anna|Boeva, Veselka|Tsiporkova, Elena', 'Department of Information Technology, Ghent University - iMinds, Gaston Crommenlaan 8 (201), 9050 Ghent, Belgium. anna.hristoskova@intec.ugent.be.|Department of Information Technology, Ghent University - iMinds, Gaston Crommenlaan 8 (201), 9050 Ghent, Belgium. anna.hristoskova@intec.ugent.be.|Department of Information Technology, Ghent University - iMinds, Gaston Crommenlaan 8 (201), 9050 Ghent, Belgium. anna.hristoskova@intec.ugent.be.', 'Belgium|Belgium|Belgium', 12, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-15-151', '24885407', 'Presently, with the increasing number and complexity of available gene expression datasets, the combination of data from multiple microarray studies addressing a similar biological question is gaining importance. The analysis and integration of multiple datasets are expected to yield more reliable and robust results since they are based on a larger number of samples and the effects of the individual study-specific biases are diminished. This is supported by recent studies suggesting that important biological signals are often preserved or enhanced by multiple experiments. An approach to combining data from different experiments is the aggregation of their clusterings into a consensus or representative clustering solution which increases the confidence in the common features of all the datasets and reveals the important differences among them.'),
(96120, 2014, 'bmc', 'Investigating perturbed pathway modules from gene expression data via structural equation models', 'Pepe, Daniele|Grassi, Mario', 'Department of Brain and Behavioural Sciences, Medical and Genomic Statistics Unit, University of Pavia, Pavia, Italy. danielepepe84@gmail.com.|Department of Brain and Behavioural Sciences, Medical and Genomic Statistics Unit, University of Pavia, Pavia, Italy. danielepepe84@gmail.com.', 'Italy|Italy', 17, 'Gene Expression|Gene Expression Profiling|Humans|Models, Genetic|Mutation|Phenotype|Signal Transduction|Ubiquitination', 'Journal Article', '10.1186/1471-2105-15-132', '24885496', 'It is currently accepted that the perturbation of complex intracellular networks, rather than the dysregulation of a single gene, is the basis for phenotypical diversity. High-throughput gene expression data allow to investigate changes in gene expression profiles among different conditions. Recently, many efforts have been made to individuate which biological pathways are perturbed, given a list of differentially expressed genes (DEGs). In order to understand these mechanisms, it is necessary to unveil the variation of genes in relation to each other, considering the different phenotypes. In this paper, we illustrate a pipeline, based on Structural Equation Modeling (SEM) that allowed to investigate pathway modules, considering not only deregulated genes but also the connections between the perturbed ones.'),
(96121, 2014, 'bmc', 'LincSNP: a database of linking disease-associated SNPs to human large intergenic non-coding RNAs', 'Ning, Shangwei|Zhao, Zuxianglan|Ye, Jingrun|Wang, Peng|Zhi, Hui|Li, Ronghong|Wang, Tingting|Li, Xia', 'Department of Brain and Behavioural Sciences, Medical and Genomic Statistics Unit, University of Pavia, Pavia, Italy. danielepepe84@gmail.com.|Department of Brain and Behavioural Sciences, Medical and Genomic Statistics Unit, University of Pavia, Pavia, Italy. danielepepe84@gmail.com.|Department of Brain and Behavioural Sciences, Medical and Genomic Statistics Unit, University of Pavia, Pavia, Italy. danielepepe84@gmail.com.|Department of Brain and Behavioural Sciences, Medical and Genomic Statistics Unit, University of Pavia, Pavia, Italy. danielepepe84@gmail.com.|Department of Brain and Behavioural Sciences, Medical and Genomic Statistics Unit, University of Pavia, Pavia, Italy. danielepepe84@gmail.com.|Department of Brain and Behavioural Sciences, Medical and Genomic Statistics Unit, University of Pavia, Pavia, Italy. danielepepe84@gmail.com.|Department of Brain and Behavioural Sciences, Medical and Genomic Statistics Unit, University of Pavia, Pavia, Italy. danielepepe84@gmail.com.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China. lixia@hrbmu.edu.cn.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|China', 36, 'Databases, Nucleic Acid|Disease|Genome-Wide Association Study|Humans|Linkage Disequilibrium|Phenotype|Polymorphism, Single Nucleotide|RNA, Long Noncoding|Software', 'Journal Article', '10.1186/1471-2105-15-152', '24885522', 'Genome-wide association studies (GWAS) have successfully identified a large number of single nucleotide polymorphisms (SNPs) that are associated with a wide range of human diseases. However, many of these disease-associated SNPs are located in non-coding regions and have remained largely unexplained. Recent findings indicate that disease-associated SNPs in human large intergenic non-coding RNA (lincRNA) may lead to susceptibility to diseases through their effects on lincRNA expression. There is, therefore, a need to specifically record these SNPs and annotate them as potential candidates for disease.'),
(96122, 2014, 'bmc', 'xcfx80BUSS: a parallel BEAST/BEAGLE utility for sequence simulation under complex evolutionary scenarios', 'Bielejec, Filip|Lemey, Philippe|Carvalho, Luiz Max|Baele, Guy|Rambaut, Andrew|Suchard, Marc A', 'Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be.|Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be.|Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be.|Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be.|Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be.|Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 13, 'Bayes Theorem|Computer Simulation|Evolution, Molecular|Monte Carlo Method|Phylogeny|Sequence Alignment|Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-15-133', '24885610', 'Simulated nucleotide or amino acid sequences are frequently used to assess the performance of phylogenetic reconstruction methods. BEAST, a Bayesian statistical framework that focuses on reconstructing time-calibrated molecular evolutionary processes, supports a wide array of evolutionary models, but lacked matching machinery for simulation of character evolution along phylogenies.'),
(96123, 2014, 'bmc', 'Improving the sensitivity of sample clustering by leveraging gene co-expression networks in variable selection', 'Wang, Zixing|San Lucas, F Anthony|Qiu, Peng|Liu, Yin', 'Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be.|Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be.|Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium. filip.bielejec@rega.kuleuven.be.|Department of Neurobiology and Anatomy, University of Texas Health Science Center at Houston, Houston, Texas, USA. yin.liu@uth.tmc.edu.', 'Belgium|Belgium|Belgium|United States', 9, 'Cluster Analysis|Colonic Neoplasms|Gene Expression Profiling|Gene Regulatory Networks|Humans|Leukemia', 'Journal Article', '10.1186/1471-2105-15-153', '24885641', 'Many variable selection techniques have been proposed for the clustering of gene expression data. While these methods tend to filter out irrelevant genes and identify informative genes that contribute to a clustering solution, they are based on criteria that do not consider the potential interactive influence among individual genes. Motivated by ensemble clustering, there is a strong interest in leveraging the structure of gene networks for gene selection, so that the relationship information between genes can be effectively utilized, while the selected genes are expected to preserve all the possible clustering structures in the data.'),
(96124, 2014, 'bmc', 'A review of machine learning methods to predict the solubility of overexpressed recombinant proteins in Escherichia coli', 'Habibi, Narjeskhatoon|Mohd Hashim, Siti Z|Norouzi, Alireza|Samian, Mohammed Razip', 'Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia. hnarjeskhatoon2@live.utm.my.|Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia. hnarjeskhatoon2@live.utm.my.|Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia. hnarjeskhatoon2@live.utm.my.|Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia. hnarjeskhatoon2@live.utm.my.', 'Malaysia|Malaysia|Malaysia|Malaysia', 16, 'Amino Acid Sequence|Artificial Intelligence|Escherichia coli|Recombinant Proteins|Solubility', 'Journal Article', '10.1186/1471-2105-15-134', '24885721', 'Over the last 20 years in biotechnology, the production of recombinant proteins has been a crucial bioprocess in both biopharmaceutical and research arena in terms of human health, scientific impact and economic volume. Although logical strategies of genetic engineering have been established, protein overexpression is still an art. In particular, heterologous expression is often hindered by low level of production and frequent fail due to opaque reasons. The problem is accentuated because there is no generic solution available to enhance heterologous overexpression. For a given protein, the extent of its solubility can indicate the quality of its function. Over 30% of synthesized proteins are not soluble. In certain experimental circumstances, including temperature, expression host, etc., protein solubility is a feature eventually defined by its sequence. Until now, numerous methods based on machine learning are proposed to predict the solubility of protein merely from its amino acid sequence. In spite of the 20 years of research on the matter, no comprehensive review is available on the published methods.'),
(96125, 2014, 'bmc', 'Combining calls from multiple somatic mutation-callers', 'Kim, Su Yeon|Jacob, Laurent|Speed, Terence P', 'Department of Statistics, University of California at Berkeley, Berkeley CA 94720, USA. suyeonkim08@gmail.com.|Department of Statistics, University of California at Berkeley, Berkeley CA 94720, USA. suyeonkim08@gmail.com.|Department of Statistics, University of California at Berkeley, Berkeley CA 94720, USA. suyeonkim08@gmail.com.', 'United States|United States|United States', 11, 'DNA Mutational Analysis|Endometrial Neoplasms|Female|Genome|Genomics|Humans|Logistic Models|Models, Statistical|Mutation', 'Journal Article', '10.1186/1471-2105-15-154', '24885750', 'Accurate somatic mutation-calling is essential for insightful mutation analyses in cancer studies. Several mutation-callers are publicly available and more are likely to appear. Nonetheless, mutation-calling is still challenging and there is unlikely to be one established caller that systematically outperforms all others. Therefore, fully utilizing multiple callers can be a powerful way to construct a list of final calls for ones research.'),
(96126, 2014, 'bmc', 'Computational approaches for isoform detection and estimation: good and bad news', 'Angelini, Claudia|De Canditiis, Daniela|De Feis, Italia', 'Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.', 'Italy|Italy|Italy', 17, 'Algorithms|Gene Expression Profiling|Humans|RNA Isoforms|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-15-135', '24885830', 'The main goal of the whole transcriptome analysis is to correctly identify all expressed transcripts within a specific cell/tissue--at a particular stage and condition--to determine their structures and to measure their abundances. RNA-seq data promise to allow identification and quantification of transcriptome at unprecedented level of resolution, accuracy and low cost. Several computational methods have been proposed to achieve such purposes. However, it is still not clear which promises are already met and which challenges are still open and require further methodological developments.'),
(96127, 2014, 'bmc', 'A method for increasing expressivity of Gene Ontology annotations using a compositional approach', 'Huntley, Rachael P|Harris, Midori A|Alam-Faruque, Yasmin|Blake, Judith A|Carbon, Seth|Dietze, Heiko|Dimmer, Emily C|Foulger, Rebecca E|Hill, David P|Khodiyar, Varsha K|Lock, Antonia|Lomax, Jane|Lovering, Ruth C|Mutowo-Meullenet, Prudence|Sawford, Tony|Van Auken, Kimberly|Wood, Valerie|Mungall, Christopher J', 'Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Istituto per le Applicazioni del Calcolo, CNR, Naples, Italy. c.angelini@iac.cnr.it.|Lawrence Berkeley National Laboratory, Genomics Division, Berkeley, CA 94720, USA. cjmungall@lbl.gov.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Ital', 41, 'Computational Biology|Gene Ontology|Humans|Molecular Sequence Annotation|Proteins', 'Journal Article', '10.1186/1471-2105-15-155', '24885854', 'The Gene Ontology project integrates data about the function of gene products across a diverse range of organisms, allowing the transfer of knowledge from model organisms to humans, and enabling computational analyses for interpretation of high-throughput experimental and clinical data. The core data structure is the annotation, an association between a gene product and a term from one of the three ontologies comprising the GO. Historically, it has not been possible to provide additional information about the context of a GO term, such as the target gene or the location of a molecular function. This has limited the specificity of knowledge that can be expressed by GO annotations.'),
(96128, 2014, 'bmc', 'MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics', 'Egea, Jose A|Henriques, David|Cokelaer, Thomas|Villaverde, Alejandro F|MacNamara, Aidan|Danciu, Diana-Patricia|Banga, Julio R|Saez-Rodriguez, Julio', 'Lawrence Berkeley National Laboratory, Genomics Division, Berkeley, CA 94720, USA. cjmungall@lbl.gov.|Lawrence Berkeley National Laboratory, Genomics Division, Berkeley, CA 94720, USA. cjmungall@lbl.gov.|Lawrence Berkeley National Laboratory, Genomics Division, Berkeley, CA 94720, USA. cjmungall@lbl.gov.|Lawrence Berkeley National Laboratory, Genomics Division, Berkeley, CA 94720, USA. cjmungall@lbl.gov.|Lawrence Berkeley National Laboratory, Genomics Division, Berkeley, CA 94720, USA. cjmungall@lbl.gov.|Lawrence Berkeley National Laboratory, Genomics Division, Berkeley, CA 94720, USA. cjmungall@lbl.gov.|(Bio)Process Engineering Group, Spanish National Research Council, IIM-CSIC, 36208 Vigo, Spain. julio@iim.csic.es.|(Bio)Process Engineering Group, Spanish National Research Council, IIM-CSIC, 36208 Vigo, Spain. julio@iim.csic.es.', 'United States|United States|United States|United States|United States|United States|Spain|Spain', 72, 'Algorithms|Bayes Theorem|Computational Biology|Metabolic Engineering|Proteomics|Software|Systems Biology', 'Journal Article', '10.1186/1471-2105-15-136', '24885957', 'Optimization is the key to solving many problems in computational biology. Global optimization methods, which provide a robust methodology, and metaheuristics in particular have proven to be the most efficient methods for many applications. Despite their utility, there is a limited availability of metaheuristic tools.'),
(96129, 2014, 'bmc', 'In silico evaluation of the influence of the translocon on partitioning of membrane segments', 'Tessier, Dominique|Laroum, Sami|Duval, Béatrice|Rath, Emma M|Church, W Bret|Hao, Jin-Kao', 'INRA, UR1268 Biopolymères Interactions et Assemblages, Nantes F-44316, France. dominique.tessier@nantes.inra.fr.|INRA, UR1268 Biopolymères Interactions et Assemblages, Nantes F-44316, France. dominique.tessier@nantes.inra.fr.|INRA, UR1268 Biopolymères Interactions et Assemblages, Nantes F-44316, France. dominique.tessier@nantes.inra.fr.|INRA, UR1268 Biopolymères Interactions et Assemblages, Nantes F-44316, France. dominique.tessier@nantes.inra.fr.|INRA, UR1268 Biopolymères Interactions et Assemblages, Nantes F-44316, France. dominique.tessier@nantes.inra.fr.|INRA, UR1268 Biopolymères Interactions et Assemblages, Nantes F-44316, France. dominique.tessier@nantes.inra.fr.', 'France|France|France|France|France|France', 0, 'Algorithms|Amino Acid Sequence|Amino Acids|Computer Simulation|Hydrophobic and Hydrophilic Interactions|Membrane Proteins|Protein Sorting Signals|Protein Structure, Secondary', 'Journal Article', '10.1186/1471-2105-15-156', '24885988', 'The locations of the TM segments inside the membrane proteins are the consequence of a cascade of several events: the localizing of the nascent chain to the membrane, its insertion through the translocon, and the conformation adopted to reach its stable state inside the lipid bilayer. Even though the hydrophobic h-region of signal peptides and a typical TM segment are both composed of mostly hydrophobic side chains, the translocon has the ability to determine whether a given segment is to be inserted into the membrane. Our goal is to acquire robust biological insights into the influence of the translocon on membrane insertion of helices, obtained from the in silico discrimination between signal peptides and transmembrane segments of bitopic proteins. Therefore, by exploiting this subtle difference, we produce an optimized scale that evaluates the tendency of each amino acid to form sequences destined for membrane insertion by the translocon.'),
(96130, 2014, 'bmc', 'New bandwidth selection criterion for Kernel PCA: approach to dimensionality reduction and classification problems', 'Thomas, Minta|De Brabanter, Kris|De Moor, Bart', 'KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Medical IT, Kasteelpark Arenberg 10, 3001 Leuven, Belgium. minta.thomas@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Medical IT, Kasteelpark Arenberg 10, 3001 Leuven, Belgium. minta.thomas@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Medical IT, Kasteelpark Arenberg 10, 3001 Leuven, Belgium. minta.thomas@esat.kuleuven.be.', 'Belgium|Belgium|Belgium', 0, 'Algorithms|Artificial Intelligence|Humans|Least-Squares Analysis|Neoplasms|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-15-137', '24886083', 'DNA microarrays are potentially powerful technology for improving diagnostic classification, treatment selection, and prognostic assessment. The use of this technology to predict cancer outcome has a history of almost a decade. Disease class predictors can be designed for known disease cases and provide diagnostic confirmation or clarify abnormal cases. The main input to this class predictors are high dimensional data with many variables and few observations. Dimensionality reduction of these features set significantly speeds up the prediction task. Feature selection and feature transformation methods are well known preprocessing steps in the field of bioinformatics. Several prediction tools are available based on these techniques.'),
(96131, 2014, 'bmc', 'Multidimensional mutual information methods for the analysis of covariation in multiple sequence alignments', 'Clark, Greg W|Ackerman, Sharon H|Tillier, Elisabeth R|Gatti, Domenico L', 'KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Medical IT, Kasteelpark Arenberg 10, 3001 Leuven, Belgium. minta.thomas@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Medical IT, Kasteelpark Arenberg 10, 3001 Leuven, Belgium. minta.thomas@esat.kuleuven.be.|Department of Medical Biophysics, University of Toronto, Campbell Family Institute for Cancer Research, Ontario Cancer Institute, University Health Network, Toronto, Ontario, Canada. e.tillier@utoronto.ca.|Department of Medical Biophysics, University of Toronto, Campbell Family Institute for Cancer Research, Ontario Cancer Institute, University Health Network, Toronto, Ontario, Canada. e.tillier@utoronto.ca.', 'Belgium|Belgium|Canada|Canada', 11, 'Models, Statistical|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-15-157', '24886131', 'Several methods are available for the detection of covarying positions from a multiple sequence alignment (MSA). If the MSA contains a large number of sequences, information about the proximities between residues derived from covariation maps can be sufficient to predict a protein fold. However, in many cases the structure is already known, and information on the covarying positions can be valuable to understand the protein mechanism and dynamic properties.'),
(96132, 2014, 'bmc', 'An R package that automatically collects and archives details for reproducible computing', 'Liu, Zhifa|Pounds, Stan', 'Department of Medical Biophysics, University of Toronto, Campbell Family Institute for Cancer Research, Ontario Cancer Institute, University Health Network, Toronto, Ontario, Canada. e.tillier@utoronto.ca.|Department of Biostatistics, St Jude Childrens Research Hospital, Memphis TN 38105, USA. stanley.pounds@stjude.org.', 'Canada|United States', 0, 'Data Interpretation, Statistical|Electronic Data Processing|Reproducibility of Results|Software', 'Journal Article', '10.1186/1471-2105-15-138', '24886202', 'It is scientifically and ethically imperative that the results of statistical analysis of biomedical research data be computationally reproducible in the sense that the reported results can be easily recapitulated from the study data. Some statistical analyses are computationally a function of many data files, program files, and other details that are updated or corrected over time. In many applications, it is infeasible to manually maintain an accurate and complete record of all these details about a particular analysis.'),
(96133, 2014, 'bmc', 'KRLMM: an adaptive genotype calling method for common and low frequency variants', 'Liu, Ruijie|Dai, Zhiyin|Yeager, Meredith|Irizarry, Rafael A|Ritchie, Matthew E', 'Department of Biostatistics, St Jude Childrens Research Hospital, Memphis TN 38105, USA. stanley.pounds@stjude.org.|Department of Biostatistics, St Jude Childrens Research Hospital, Memphis TN 38105, USA. stanley.pounds@stjude.org.|Department of Biostatistics, St Jude Childrens Research Hospital, Memphis TN 38105, USA. stanley.pounds@stjude.org.|Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia. rafa@jimmy.harvard.edu.|Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia. rafa@jimmy.harvard.edu.', 'United States|United States|United States|Australia|Australia', 3, 'Adaptation, Biological|Algorithms|Alleles|Cluster Analysis|Gene Frequency|Genotype|Genotyping Techniques|HapMap Project|Humans|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-15-158', '24886250', 'SNP genotyping microarrays have revolutionized the study of complex disease. The current range of commercially available genotyping products contain extensive catalogues of low frequency and rare variants. Existing SNP calling algorithms have difficulty dealing with these low frequency variants, as the underlying models rely on each genotype having a reasonable number of observations to ensure accurate clustering.'),
(96134, 2014, 'bmc', 'WebChem Viewer: a tool for the easy dissemination of chemical and structural data sets', 'Durrant, Jacob D|Amaro, Rommie E', 'Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia. rafa@jimmy.harvard.edu.|Department of Chemistry & Biochemistry and the National Biomedical Computation Resource, University of California, San Diego, La Jolla, CA 92093, USA. ramaro@ucsd.edu.', 'Australia|United States', 0, 'Drug Discovery|Internet|Molecular Structure|Pharmaceutical Preparations|Software', 'Journal Article', '10.1186/1471-2105-15-159', '24886360', 'Sharing sets of chemical data (e.g., chemical properties, docking scores, etc.) among collaborators with diverse skill sets is a common task in computer-aided drug design and medicinal chemistry. The ability to associate this data with images of the relevant molecular structures greatly facilitates scientific communication. There is a need for a simple, free, open-source program that can automatically export aggregated reports of entire chemical data sets to files viewable on any computer, regardless of the operating system and without requiring the installation of additional software.'),
(96135, 2014, 'bmc', 'Ciruvis: a web-based tool for rule networks and interaction detection using rule-based classifiers', 'Bornelöv, Susanne|Marillet, Simon|Komorowski, Jan', 'Department of Chemistry & Biochemistry and the National Biomedical Computation Resource, University of California, San Diego, La Jolla, CA 92093, USA. ramaro@ucsd.edu.|Department of Chemistry & Biochemistry and the National Biomedical Computation Resource, University of California, San Diego, La Jolla, CA 92093, USA. ramaro@ucsd.edu.|Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, 751 24 Uppsala, Sweden. jan.komorowski@icm.uu.se.', 'United States|United States|Sweden', 0, 'Algorithms|Classification|Humans|Internet|Leukemia|Lymphoma|Software', 'Journal Article', '10.1186/1471-2105-15-139', '24886370', 'The use of classification algorithms is becoming increasingly important for the field of computational biology. However, not only the quality of the classification, but also its biological interpretation is important. This interpretation may be eased if interacting elements can be identified and visualized, something that requires appropriate tools and methods.'),
(96136, 2014, 'bmc', 'On the necessity of dissecting sequence similarity scores into segment-specific contributions for inferring protein homology, function prediction and annotation', 'Wong, Wing-Cheong|Maurer-Stroh, Sebastian|Eisenhaber, Birgit|Eisenhaber, Frank', 'Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore. wongwc@bii.a-star.edu.sg.|Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore. wongwc@bii.a-star.edu.sg.|Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore. wongwc@bii.a-star.edu.sg.|Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore. wongwc@bii.a-star.edu.sg.', 'Singapore|Singapore|Singapore|Singapore', 0, 'Amino Acid Sequence|Animals|Conserved Sequence|Humans|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1186/1471-2105-15-166', '24890864', 'Protein sequence similarities to any types of non-globular segments (coiled coils, low complexity regions, transmembrane regions, long loops, etc. where either positional sequence conservation is the result of a very simple, physically induced pattern or rather integral sequence properties are critical) are pertinent sources for mistaken homologies. Regretfully, these considerations regularly escape attention in large-scale annotation studies since, often, there is no substitute to manual handling of these cases. Quantitative criteria are required to suppress events of function annotation transfer as a result of false homology assignments.'),
(96137, 2014, 'bmc', 'PVT: an efficient computational procedure to speed up next-generation sequence analysis', 'Maji, Ranjan Kumar|Sarkar, Arijita|Khatua, Sunirmal|Dasgupta, Subhasis|Ghosh, Zhumur', 'Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore. wongwc@bii.a-star.edu.sg.|Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore. wongwc@bii.a-star.edu.sg.|Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore. wongwc@bii.a-star.edu.sg.|Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore. wongwc@bii.a-star.edu.sg.|Bioinformatics Centre, Bose Institute, Kolkata 700054, India. zhumur@jcbose.ac.in.', 'Singapore|Singapore|Singapore|Singapore|India', 0, 'Genomics|High-Throughput Nucleotide Sequencing|Humans|Software|Time Factors', 'Journal Article', '10.1186/1471-2105-15-167', '24894600', 'High-throughput Next-Generation Sequencing (NGS) techniques are advancing genomics and molecular biology research. This technology generates substantially large data which puts up a major challenge to the scientists for an efficient, cost and time effective solution to analyse such data. Further, for the different types of NGS data, there are certain common challenging steps involved in analysing those data. Spliced alignment is one such fundamental step in NGS data analysis which is extremely computational intensive as well as time consuming. There exists serious problem even with the most widely used spliced alignment tools. TopHat is one such widely used spliced alignment tools which although supports multithreading, does not efficiently utilize computational resources in terms of CPU utilization and memory. Here we have introduced PVT (Pipelined Version of TopHat) where we take up a modular approach by breaking TopHats serial execution into a pipeline of multiple stages, thereby increasing the degree of parallelization and computational resource utilization. Thus we address the discrepancies in TopHat so as to analyze large NGS data efficiently.'),
(96138, 2014, 'bmc', 'Exposure time independent summary statistics for assessment of drug dependent cell line growth inhibition', 'Falgreen, Steffen|Laursen, Maria Bach|Bødker, Julie Støve|Kjeldsen, Malene Krag|Schmitz, Alexander|Nyegaard, Mette|Johnsen, Hans Erik|Dybkær, Karen|Bøgsted, Martin', 'Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 0, 'Cell Cycle|Cell Line, Tumor|Cell Proliferation|Growth Inhibitors|Humans|Kinetics|Models, Theoretical|Neoplasms|Regression Analysis|Time Factors', 'Journal Article', '10.1186/1471-2105-15-168', '24902483', 'In vitro generated dose-response curves of human cancer cell lines are widely used to develop new therapeutics. The curves are summarised by simplified statistics that ignore the conventionally used dose-response curves dependency on drug exposure time and growth kinetics. This may lead to suboptimal exploitation of data and biased conclusions on the potential of the drug in question. Therefore we set out to improve the dose-response assessments by eliminating the impact of time dependency.'),
(96139, 2014, 'bmc', 'A semi-automated technique for labeling and counting of apoptosing retinal cells', 'Bizrah, Mukhtar|Dakin, Steve C|Guo, Li|Rahman, Farzana|Parnell, Miles|Normando, Eduardo|Nizari, Shereen|Davis, Benjamin|Younis, Ahmed|Cordeiro, M Francesca', 'Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Department of Haematology, Aalborg University Hospital, Aalborg, Denmark. sfl@rn.dk.|Glaucoma and Retinal Neurodegeneration Group, UCL Institute of Ophthalmology, London, UK. m.cordeiro@ucl.ac.uk.', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|United Kingdom', 16, 'Algorithms|Apoptosis|Automation, Laboratory|Cell Count|Glaucoma|Humans|Retinal Ganglion Cells', 'Journal Article', '10.1186/1471-2105-15-169', '24902592', 'Retinal ganglion cell (RGC) loss is one of the earliest and most important cellular changes in glaucoma. The DARC (Detection of Apoptosing Retinal Cells) technology enables in vivo real-time non-invasive imaging of single apoptosing retinal cells in animal models of glaucoma and Alzheimers disease. To date, apoptosing RGCs imaged using DARC have been counted manually. This is time-consuming, labour-intensive, vulnerable to bias, and has considerable inter- and intra-operator variability.'),
(96140, 2014, 'bmc', 'Ensemble analyses improve signatures of tumour hypoxia and reveal inter-platform differences', 'Fox, Natalie S|Starmans, Maud H W|Haider, Syed|Lambin, Philippe|Boutros, Paul C', 'Glaucoma and Retinal Neurodegeneration Group, UCL Institute of Ophthalmology, London, UK. m.cordeiro@ucl.ac.uk.|Glaucoma and Retinal Neurodegeneration Group, UCL Institute of Ophthalmology, London, UK. m.cordeiro@ucl.ac.uk.|Glaucoma and Retinal Neurodegeneration Group, UCL Institute of Ophthalmology, London, UK. m.cordeiro@ucl.ac.uk.|Glaucoma and Retinal Neurodegeneration Group, UCL Institute of Ophthalmology, London, UK. m.cordeiro@ucl.ac.uk.|Informatics and Bio-computing Platform, Ontario Institute for Cancer Research, Toronto, Canada. Paul.Boutros@oicr.on.ca.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|Canada', 11, 'Algorithms|Cell Hypoxia|Gene Expression Regulation, Neoplastic|Humans|Neoplasms|Prognosis|Reproducibility of Results|Tissue Array Analysis', 'Journal Article', '10.1186/1471-2105-15-170', '24902696', 'The reproducibility of transcriptomic biomarkers across datasets remains poor, limiting clinical application. We and others have suggested that this is in-part caused by differential error-structure between datasets, and their incomplete removal by pre-processing algorithms.'),
(96141, 2014, 'bmc', 'Scoring docking conformations using predicted protein interfaces', 'Esmaielbeiki, Reyhaneh|Nebel, Jean-Christophe', 'Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK. Reyhaneh.Esmaielbeiki@dtc.ox.ac.uk.|Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK. Reyhaneh.Esmaielbeiki@dtc.ox.ac.uk.', 'United Kingdom|United Kingdom', 0, 'Models, Molecular|Protein Binding|Protein Interaction Domains and Motifs|Proteins|Software', 'Journal Article', '10.1186/1471-2105-15-171', '24906633', 'Since proteins function by interacting with other molecules, analysis of protein-protein interactions is essential for comprehending biological processes. Whereas understanding of atomic interactions within a complex is especially useful for drug design, limitations of experimental techniques have restricted their practical use. Despite progress in docking predictions, there is still room for improvement. In this study, we contribute to this topic by proposing T-PioDock, a framework for detection of a native-like docked complex 3D structure. T-PioDock supports the identification of near-native conformations from 3D models that docking software produced by scoring those models using binding interfaces predicted by the interface predictor, Template based Protein Interface Prediction (T-PIP).'),
(96142, 2014, 'bmc', 'hsphase: an R package for pedigree reconstruction, detection of recombination events, phasing and imputation of half-sib family groups', 'Ferdosi, Mohammad H|Kinghorn, Brian P|van der Werf, Julius H J|Lee, Seung Hwan|Gondro, Cedric', 'The Centre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, Australia. mferdosi@myune.edu.au.|The Centre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, Australia. mferdosi@myune.edu.au.|The Centre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, Australia. mferdosi@myune.edu.au.|The Centre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, Australia. mferdosi@myune.edu.au.|The Centre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, Australia. mferdosi@myune.edu.au.', 'Australia|Australia|Australia|Australia|Australia', 20, 'Animals|Cattle|Genetic Markers|Genome|Genomics|Genotype|Haplotypes|Homozygote|Humans|Pedigree|Polymorphism, Single Nucleotide|Recombination, Genetic|Sheep', 'Journal Article', '10.1186/1471-2105-15-172', '24906803', 'Identification of recombination events and which chromosomal segments contributed to an individual is useful for a number of applications in genomic analyses including haplotyping, imputation, signatures of selection, and improved estimates of relationship and probability of identity by descent. Genotypic data on half-sib family groups are widely available in livestock genomics. This structure makes it possible to identify recombination events accurately even with only a few individuals and it lends itself well to a range of applications such as parentage assignment and pedigree verification.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96143, 2014, 'bmc', 'MiningABs: mining associated biomarkers across multi-connected gene expression datasets', 'Cheng, Chun-Pei|DeBoever, Christopher|Frazer, Kelly A|Liu, Yu-Cheng|Tseng, Vincent S', 'The Centre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, Australia. mferdosi@myune.edu.au.|The Centre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, Australia. mferdosi@myune.edu.au.|Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan. kafrazer@ucsd.edu.|Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan. kafrazer@ucsd.edu.|Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan. kafrazer@ucsd.edu.', 'Australia|Australia|-|-|-', 0, 'Algorithms|Biomarkers, Tumor|Data Mining|Gene Expression|Gene Expression Profiling|Genetic Markers|Humans|Neoplasms', 'Journal Article', '10.1186/1471-2105-15-173', '24909518', 'Human disease often arises as a consequence of alterations in a set of associated genes rather than alterations to a set of unassociated individual genes. Most previous microarray-based meta-analyses identified disease-associated genes or biomarkers independent of genetic interactions. Therefore, in this study, we present the first meta-analysis method capable of taking gene combination effects into account to efficiently identify associated biomarkers (ABs) across different microarray platforms.'),
(96144, 2014, 'bmc', 'Scan for Motifs: a webserver for the analysis of post-transcriptional regulatory elements in the 3 untranslated regions (3 UTRs) of mRNAs', 'Biswas, Ambarish|Brown, Chris M', 'Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan. kafrazer@ucsd.edu.|Department of Biochemistry, Genetics Otago, University of Otago, Dunedin, New Zealand. chris.brown@otago.ac.nz.', '-|New Zealand', 7, '3 Untranslated Regions|Animals|Humans|RNA Stability|RNA, Messenger|Regulatory Elements, Transcriptional|Software', 'Journal Article', '10.1186/1471-2105-15-174', '24909639', 'Gene expression in vertebrate cells may be controlled post-transcriptionally through regulatory elements in mRNAs. These are usually located in the untranslated regions (UTRs) of mRNA sequences, particularly the 3UTRs.'),
(96145, 2014, 'bmc', 'SMARTPOP: inferring the impact of social dynamics on genetic diversity through high speed simulations', 'Guillot, Elsa G|Cox, Murray P', 'Department of Biochemistry, Genetics Otago, University of Otago, Dunedin, New Zealand. chris.brown@otago.ac.nz.|Statistics and Bioinformatics Group, Institute of Fundamental Sciences, Massey University Palmerston North, New Zealand. m.p.cox@massey.ac.nz.', 'New Zealand|New Zealand', 0, 'Bayes Theorem|Computer Simulation|DNA, Mitochondrial|Evolution, Molecular|Genetic Variation|Genetics, Population|Humans|Models, Genetic|Social Behavior|Software Design', 'Journal Article', '10.1186/1471-2105-15-175', '24913447', 'Social behavior has long been known to influence patterns of genetic diversity, but the effect of social processes on population genetics remains poorly quantified - partly due to limited community-level genetic sampling (which is increasingly being remedied), and partly to a lack of fast simulation software to jointly model genetic evolution and complex social behavior, such as marriage rules.'),
(96146, 2014, 'bmc', 'QMachine: commodity supercomputing in web browsers', 'Wilkinson, Sean R|Almeida, Jonas S', 'Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, USA. wilkinson@uab.edu.|Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, USA. wilkinson@uab.edu.', 'United States|United States', 0, 'Computational Biology|Genome|Genomics|Humans|Software Design|Streptococcus pneumoniae|Web Browser', 'Journal Article', '10.1186/1471-2105-15-176', '24913605', 'Ongoing advancements in cloud computing provide novel opportunities in scientific computing, especially for distributed workflows. Modern web browsers can now be used as high-performance workstations for querying, processing, and visualizing genomics Big Data from sources like The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) without local software installation or configuration. The design of QMachine (QM) was driven by the opportunity to use this pervasive computing model in the context of the Web of Linked Data in Biomedicine.'),
(96147, 2014, 'bmc', 'Integrating the interactome and the transcriptome of Drosophila', 'Murali, Thilakam|Pacifico, Svetlana|Finley, Russell L', 'Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, USA. wilkinson@uab.edu.|Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, USA. wilkinson@uab.edu.|Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Michigan 48201, USA. rfinley@wayne.edu.', 'United States|United States|United States', 1, 'Animals|Drosophila Proteins|Drosophila melanogaster|Gene Expression|Humans|Organ Specificity|Protein Binding|Protein Interaction Maps|Transcription Factors|Transcriptome', 'Journal Article', '10.1186/1471-2105-15-177', '24913703', 'Networks of interacting genes and gene products mediate most cellular and developmental processes. High throughput screening methods combined with literature curation are identifying many of the protein-protein interactions (PPI) and protein-DNA interactions (PDI) that constitute these networks. Most of the detection methods, however, fail to identify the in vivo spatial or temporal context of the interactions. Thus, the interaction data are a composite of the individual networks that may operate in specific tissues or developmental stages. Genome-wide expression data may be useful for filtering interaction data to identify the subnetworks that operate in specific spatial or temporal contexts. Here we take advantage of the extensive interaction and expression data available for Drosophila to analyze how interaction networks may be unique to specific tissues and developmental stages.'),
(96148, 2014, 'bmc', 'PBHoney: identifying genomic variants via long-read discordance and interrupted mapping', 'English, Adam C|Salerno, William J|Reid, Jeffrey G', 'Human Genome Sequencing Center at Baylor College of Medicine, One Baylor Plaza, Houston 77030, Texas, USA. english@bcm.edu.|Human Genome Sequencing Center at Baylor College of Medicine, One Baylor Plaza, Houston 77030, Texas, USA. english@bcm.edu.|Human Genome Sequencing Center at Baylor College of Medicine, One Baylor Plaza, Houston 77030, Texas, USA. english@bcm.edu.', 'United States|United States|United States', 0, 'Escherichia coli|Gene Deletion|Genome|Genomics|High-Throughput Nucleotide Sequencing|Humans|INDEL Mutation|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-15-180', '24915764', 'As resequencing projects become more prevalent across a larger number of species, accurate variant identification will further elucidate the nature of genetic diversity and become increasingly relevant in genomic studies. However, the identification of larger genomic variants via DNA sequencing is limited by both the incomplete information provided by sequencing reads and the nature of the genome itself. Long-read sequencing technologies provide high-resolution access to structural variants often inaccessible to shorter reads.'),
(96149, 2014, 'bmc', 'Spot quantification in two dimensional gel electrophoresis image analysis: comparison of different approaches and presentation of a novel compound fitting algorithm', 'Brauner, Jan M|Groemer, Teja W|Stroebel, Armin|Grosse-Holz, Simon|Oberstein, Timo|Wiltfang, Jens|Kornhuber, Johannes|Maler, Juan Manuel', 'Department of Psychiatry and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nuremberg, Schwabachanlage 6, 091054 Erlangen, Germany. jan.brauner@gmx.de.|Department of Psychiatry and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nuremberg, Schwabachanlage 6, 091054 Erlangen, Germany. jan.brauner@gmx.de.|Department of Psychiatry and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nuremberg, Schwabachanlage 6, 091054 Erlangen, Germany. jan.brauner@gmx.de.|Department of Psychiatry and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nuremberg, Schwabachanlage 6, 091054 Erlangen, Germany. jan.brauner@gmx.de.|Department of Psychiatry and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nuremberg, Schwabachanlage 6, 091054 Erlangen, Germany. jan.brauner@gmx.de.|Department of Psychiatry and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nuremberg, Schwabachanlage 6, 091054 Erlangen, Germany. jan.brauner@gmx.de.|Department of Psychiatry and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nuremberg, Schwabachanlage 6, 091054 Erlangen, Germany. jan.brauner@gmx.de.|Department of Psychiatry and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nuremberg, Schwabachanlage 6, 091054 Erlangen, Germany. jan.brauner@gmx.de.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Alzheimer Disease|Electrophoresis, Gel, Two-Dimensional|Humans|Image Processing, Computer-Assisted|Normal Distribution|Proteins', 'Comparative Study', '10.1186/1471-2105-15-181', '24915860', 'Various computer-based methods exist for the detection and quantification of protein spots in two dimensional gel electrophoresis images. Area-based methods are commonly used for spot quantification: an area is assigned to each spot and the sum of the pixel intensities in that area, the so-called volume, is used a measure for spot signal. Other methods use the optical density, i.e. the intensity of the most intense pixel of a spot, or calculate the volume from the parameters of a fitted function.'),
(96150, 2014, 'bmc', 'Design of a flexible component gathering algorithm for converting cell-based models to graph representations for use in evolutionary search', 'Budnikova, Marianna|Habig, Jeffrey W|Lobo, Daniel|Cornia, Nicolas|Levin, Michael|Andersen, Tim', 'Department of Psychiatry and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nuremberg, Schwabachanlage 6, 091054 Erlangen, Germany. jan.brauner@gmx.de.|Department of Computer Science, Boise State University, 1910 University Drive, Boise, ID 83725, USA. jeffreyhabig@boisestate.edu.|Department of Computer Science, Boise State University, 1910 University Drive, Boise, ID 83725, USA. jeffreyhabig@boisestate.edu.|Department of Computer Science, Boise State University, 1910 University Drive, Boise, ID 83725, USA. jeffreyhabig@boisestate.edu.|Department of Computer Science, Boise State University, 1910 University Drive, Boise, ID 83725, USA. jeffreyhabig@boisestate.edu.|Department of Computer Science, Boise State University, 1910 University Drive, Boise, ID 83725, USA. jeffreyhabig@boisestate.edu.', 'Germany|United States|United States|United States|United States|United States', 1, 'Algorithms|Animals|Evolution, Molecular|Humans|Models, Biological|Planarians|Regeneration', 'Journal Article', '10.1186/1471-2105-15-178', '24917489', 'The ability of science to produce experimental data has outpaced the ability to effectively visualize and integrate the data into a conceptual framework that can further higher order understanding. Multidimensional and shape-based observational data of regenerative biology presents a particularly daunting challenge in this regard. Large amounts of data are available in regenerative biology, but little progress has been made in understanding how organisms such as planaria robustly achieve and maintain body form. An example of this kind of data can be found in a new repository (PlanformDB) that encodes descriptions of planaria experiments and morphological outcomes using a graph formalism.'),
(96151, 2014, 'bmc', 'A novel method for gathering and prioritizing disease candidate genes based on construction of a set of disease-related MeSH® terms', 'Ono, Toshihide|Kuhara, Satoru', 'Department of Computer Science, Boise State University, 1910 University Drive, Boise, ID 83725, USA. jeffreyhabig@boisestate.edu.|Department of Genetic Resources Technology, Faculty of Agriculture, Kyushu University, 6-10-1 Hakozaki Higashi-ku, Fukuoka 812-8581, Japan. kuhara@grt.kyushu-u.ac.jp.', 'United States|Japan', 0, 'Alzheimer Disease|Animals|Computational Biology|Databases, Factual|Gene Expression Regulation|Humans|Medical Subject Headings|Pain', 'Journal Article', '10.1186/1471-2105-15-179', '24917541', 'Understanding the molecular mechanisms involved in disease is critical for the development of more effective and individualized strategies for prevention and treatment. The amount of disease-related literature, including new genetic information on the molecular mechanisms of disease, is rapidly increasing. Extracting beneficial information from literature can be facilitated by computational methods such as the knowledge-discovery approach. Several methods for mining gene-disease relationships using computational methods have been developed, however, there has been a lack of research evaluating specific disease candidate genes.'),
(96152, 2014, 'bmc', 'Insights into mechanism kinematics for protein motion simulation', 'Diez, Mikel|Petuya, Víctor|Martínez-Cruz, Luis Alfonso|Hernández, Alfonso', 'Faculty of Engineering in Bilbao, University of the Basque Country UPV/EHU, Department of Mechanical Engineering, Alameda de Urquijo s/n, 48013 Bilbao, Spain. mikel.diez@ehu.es.|Faculty of Engineering in Bilbao, University of the Basque Country UPV/EHU, Department of Mechanical Engineering, Alameda de Urquijo s/n, 48013 Bilbao, Spain. mikel.diez@ehu.es.|Faculty of Engineering in Bilbao, University of the Basque Country UPV/EHU, Department of Mechanical Engineering, Alameda de Urquijo s/n, 48013 Bilbao, Spain. mikel.diez@ehu.es.|Faculty of Engineering in Bilbao, University of the Basque Country UPV/EHU, Department of Mechanical Engineering, Alameda de Urquijo s/n, 48013 Bilbao, Spain. mikel.diez@ehu.es.', 'Spain|Spain|Spain|Spain', 0, 'Algorithms|Kinetics|Models, Molecular|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1186/1471-2105-15-184', '24923224', 'The high demanding computational requirements necessary to carry out protein motion simulations make it difficult to obtain information related to protein motion. On the one hand, molecular dynamics simulation requires huge computational resources to achieve satisfactory motion simulations. On the other hand, less accurate procedures such as interpolation methods, do not generate realistic morphs from the kinematic point of view. Analyzing a proteins movement is very similar to serial robots, thus, it is possible to treat the protein chain as a serial mechanism composed of rotational degrees of freedom. Recently, based on this hypothesis, new methodologies have arisen, based on mechanism and robot kinematics, to simulate protein motion. Probabilistic roadmap method, which discretizes the protein configurational space against a scoring function, or the kinetostatic compliance method that minimizes the torques that appear in bonds, aim to simulate protein motion with a reduced computational cost.'),
(96153, 2014, 'bmc', 'Detecting contaminated birthdates using generalized additive models', 'Luo, Wei|Gallagher, Marcus|Loveday, Bill|Ballantyne, Susan|Connor, Jason P|Wiles, Janet', 'Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, Australia. wei.luo@deakin.edu.au.|Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, Australia. wei.luo@deakin.edu.au.|Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, Australia. wei.luo@deakin.edu.au.|Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, Australia. wei.luo@deakin.edu.au.|Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, Australia. wei.luo@deakin.edu.au.|Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, Australia. wei.luo@deakin.edu.au.', 'Australia|Australia|Australia|Australia|Australia|Australia', 1, 'Ageism|Databases, Factual|False Positive Reactions|Humans|Models, Theoretical|Oxycodone|Pain|Public Health', 'Journal Article', '10.1186/1471-2105-15-185', '24923281', 'Erroneous patient birthdates are common in health databases. Detection of these errors usually involves manual verification, which can be resource intensive and impractical. By identifying a frequent manifestation of birthdate errors, this paper presents a principled and statistically driven procedure to identify erroneous patient birthdates.'),
(96154, 2014, 'bmc', 'Skewer: a fast and accurate adapter trimmer for next-generation sequencing paired-end reads', 'Jiang, Hongshan|Lei, Rong|Ding, Shou-Wei|Zhu, Shuifang', 'Institute of Plant Quarantine Research, Chinese Academy of Inspection and Quarantine, Huixinli 241, Beijing, 100029 China. hongshan.jiang@gmail.com.|Institute of Plant Quarantine Research, Chinese Academy of Inspection and Quarantine, Huixinli 241, Beijing, 100029 China. hongshan.jiang@gmail.com.|Institute of Plant Quarantine Research, Chinese Academy of Inspection and Quarantine, Huixinli 241, Beijing, 100029 China. hongshan.jiang@gmail.com.|Institute of Plant Quarantine Research, Chinese Academy of Inspection and Quarantine, Huixinli 241, Beijing, 100029 China. hongshan.jiang@gmail.com.', 'China|China|China|China', 375, 'Algorithms|Animals|Arabidopsis|Caenorhabditis elegans|Drosophila|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, RNA|Software|Time Factors', 'Journal Article', '10.1186/1471-2105-15-182', '24925680', 'Adapter trimming is a prerequisite step for analyzing next-generation sequencing (NGS) data when the reads are longer than the target DNA/RNA fragments. Although typically used in small RNA sequencing, adapter trimming is also used widely in other applications, such as genome DNA sequencing and transcriptome RNA/cDNA sequencing, where fragments shorter than a read are sometimes obtained because of the limitations of NGS protocols. For the newly emerged Nextera long mate-pair (LMP) protocol, junction adapters are located in the middle of all properly constructed fragments, hence, adapter trimming is essential to gain the correct paired reads. However, our investigations have shown that few adapter trimming tools meet both efficiency and accuracy requirements simultaneously. The performances of these tools can be even worse for paired-end and/or mate-pair sequencing.'),
(96155, 2014, 'bmc', 'LUSt: a tool for approximated maximum likelihood supertree reconstruction', 'Akanni, Wasiu A|Creevey, Christopher J|Wilkinson, Mark|Pisani, Davide', 'Institute of Plant Quarantine Research, Chinese Academy of Inspection and Quarantine, Huixinli 241, Beijing, 100029 China. hongshan.jiang@gmail.com.|Institute of Plant Quarantine Research, Chinese Academy of Inspection and Quarantine, Huixinli 241, Beijing, 100029 China. hongshan.jiang@gmail.com.|Institute of Plant Quarantine Research, Chinese Academy of Inspection and Quarantine, Huixinli 241, Beijing, 100029 China. hongshan.jiang@gmail.com.|Department of Biology, The National University of Ireland, Maynooth, Maynooth, Kildare, Ireland. davide.pisani@bristol.ac.uk.', 'China|China|China|Ireland', 0, 'Algorithms|Animals|Genomics|Humans|Likelihood Functions', 'Journal Article', '10.1186/1471-2105-15-183', '24925766', 'Supertrees combine disparate, partially overlapping trees to generate a synthesis that provides a high level perspective that cannot be attained from the inspection of individual phylogenies. Supertrees can be seen as meta-analytical tools that can be used to make inferences based on results of previous scientific studies. Their meta-analytical application has increased in popularity since it was realised that the power of statistical tests for the study of evolutionary trends critically depends on the use of taxon-dense phylogenies. Further to that, supertrees have found applications in phylogenomics where they are used to combine gene trees and recover species phylogenies based on genome-scale data sets.'),
(96156, 2014, 'bmc', 'Assessment and refinement of eukaryotic gene structure prediction with gene-structure-aware multiple protein sequence alignment', 'Gotoh, Osamu|Morita, Mariko|Nelson, David R', 'Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo 135-0064, Japan. o.gotoh@aist.go.jp.|Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo 135-0064, Japan. o.gotoh@aist.go.jp.|Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo 135-0064, Japan. o.gotoh@aist.go.jp.', 'Japan|Japan|Japan', 0, 'Algorithms|Genome, Plant|High-Throughput Nucleotide Sequencing|Introns|Plant Proteins|Pseudogenes|Reproducibility of Results|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-15-189', '24927652', 'Accurate computational identification of eukaryotic gene organization is a long-standing problem. Despite the fundamental importance of precise annotation of genes encoded in newly sequenced genomes, the accuracy of predicted gene structures has not been critically evaluated, mostly due to the scarcity of proper assessment methods.'),
(96157, 2014, 'bmc', 'Detecting overlapping protein complexes based on a generative model with functional and topological properties', 'Zhang, Xiao-Fei|Dai, Dao-Qing|Ou-Yang, Le|Yan, Hong', 'Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo 135-0064, Japan. o.gotoh@aist.go.jp.|Intelligent Data Center and Department of Mathematics, Sun Yat-Sen University, Xingang Road West, 510275 Guangzhou, China. stsddq@mail.sysu.edu.cn.|Intelligent Data Center and Department of Mathematics, Sun Yat-Sen University, Xingang Road West, 510275 Guangzhou, China. stsddq@mail.sysu.edu.cn.|Intelligent Data Center and Department of Mathematics, Sun Yat-Sen University, Xingang Road West, 510275 Guangzhou, China. stsddq@mail.sysu.edu.cn.', 'Japan|China|China|China', 27, 'Algorithms|Humans|Models, Biological|Probability|Protein Interaction Mapping|Proteins|Software', 'Journal Article', '10.1186/1471-2105-15-186', '24928559', 'Identification of protein complexes can help us get a better understanding of cellular mechanism. With the increasing availability of large-scale protein-protein interaction (PPI) data, numerous computational approaches have been proposed to detect complexes from the PPI networks. However, most of the current approaches do not consider overlaps among complexes or functional annotation information of individual proteins. Therefore, they might not be able to reflect the biological reality faithfully or make full use of the available domain-specific knowledge.'),
(96158, 2014, 'bmc', 'Mapping biological entities using the longest approximately common prefix method', 'Rudniy, Alex|Song, Min|Geller, James', 'Intelligent Data Center and Department of Mathematics, Sun Yat-Sen University, Xingang Road West, 510275 Guangzhou, China. stsddq@mail.sysu.edu.cn.|Department of Library and Information Science, Yonsei University, 50 Yonsei-ro, Seoul 120-749, Korea. min.song@yonsei.ac.kr.|Department of Library and Information Science, Yonsei University, 50 Yonsei-ro, Seoul 120-749, Korea. min.song@yonsei.ac.kr.', 'China|-|-', 0, 'Algorithms|Computational Biology|Computer Graphics|Humans|Language|Natural Language Processing|Terminology as Topic|Unified Medical Language System', 'Journal Article', '10.1186/1471-2105-15-187', '24928653', 'The significant growth in the volume of electronic biomedical data in recent decades has pointed to the need for approximate string matching algorithms that can expedite tasks such as named entity recognition, duplicate detection, terminology integration, and spelling correction. The task of source integration in the Unified Medical Language System (UMLS) requires considerable expert effort despite the presence of various computational tools. This problem warrants the search for a new method for approximate string matching and its UMLS-based evaluation.'),
(96159, 2014, 'bmc', 'An integrative method to normalize RNA-Seq data', 'Filloux, Cyril|Cédric, Meersseman|Romain, Philippe|Lionel, Forestier|Christophe, Klopp|Dominique, Rocha|Abderrahman, Maftah|Daniel, Petit', 'Department of Library and Information Science, Yonsei University, 50 Yonsei-ro, Seoul 120-749, Korea. min.song@yonsei.ac.kr.|Department of Library and Information Science, Yonsei University, 50 Yonsei-ro, Seoul 120-749, Korea. min.song@yonsei.ac.kr.|Department of Library and Information Science, Yonsei University, 50 Yonsei-ro, Seoul 120-749, Korea. min.song@yonsei.ac.kr.|Department of Library and Information Science, Yonsei University, 50 Yonsei-ro, Seoul 120-749, Korea. min.song@yonsei.ac.kr.|Department of Library and Information Science, Yonsei University, 50 Yonsei-ro, Seoul 120-749, Korea. min.song@yonsei.ac.kr.|Department of Library and Information Science, Yonsei University, 50 Yonsei-ro, Seoul 120-749, Korea. min.song@yonsei.ac.kr.|Department of Library and Information Science, Yonsei University, 50 Yonsei-ro, Seoul 120-749, Korea. min.song@yonsei.ac.kr.|INRA, UMR1061, Unité Génétique Moléculaire Animale, 123 avenue Albert Thomas, F-87060 Limoges Cedex, France. daniel.petit@unilim.fr.', '-|-|-|-|-|-|-|France', 7, 'Animals|Calibration|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|RNA|Sequence Analysis, RNA|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-15-188', '24929920', 'Transcriptome sequencing is a powerful tool for measuring gene expression, but as well as some other technologies, various artifacts and biases affect the quantification. In order to correct some of them, several normalization approaches have emerged, differing both in the statistical strategy employed and in the type of corrected biases. However, there is no clear standard normalization method.'),
(96160, 2014, 'bmc', 'Determination of sample size for a multi-class classifier based on single-nucleotide polymorphisms: a volume under the surface approach', 'Liu, Xinyu|Wang, Yupeng|Sriram, T N', 'INRA, UMR1061, Unité Génétique Moléculaire Animale, 123 avenue Albert Thomas, F-87060 Limoges Cedex, France. daniel.petit@unilim.fr.|INRA, UMR1061, Unité Génétique Moléculaire Animale, 123 avenue Albert Thomas, F-87060 Limoges Cedex, France. daniel.petit@unilim.fr.|Department of Statistics, University of Georgia, Athens, GA 30602, USA. tn@uga.edu.', 'France|France|Georgia', 1, 'Bayes Theorem|Humans|Monte Carlo Method|Polymorphism, Single Nucleotide|ROC Curve|Sample Size', 'Journal Article', '10.1186/1471-2105-15-190', '24930009', 'Data on single-nucleotide polymorphisms (SNPs) have been found to be useful in predicting phenotypes ranging from an individuals class membership to his/her risk of developing a disease. In multi-class classification scenarios, clinical samples are often limited due to cost constraints, making it necessary to determine the sample size needed to build an accurate classifier based on SNPs. The performance of such classifiers can be assessed using the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) for two classes and the Volume Under the ROC hyper-Surface (VUS) for three or more classes. Sample size determination based on AUC or VUS would not only guarantee an overall correct classification rate, but also make studies more cost-effective.'),
(96161, 2014, 'bmc', 'Efficient design of meganucleases using a machine learning approach', 'Zaslavskiy, Mikhail|Bertonati, Claudia|Duchateau, Philippe|Duclert, Aymeric|Silva, George H', 'Department of Statistics, University of Georgia, Athens, GA 30602, USA. tn@uga.edu.|Department of Statistics, University of Georgia, Athens, GA 30602, USA. tn@uga.edu.|Research and Development department, Cellectis, 8 rue de la Croix Jarry, Paris 75013, France. philippe.duchateau@cellectis.com.|Research and Development department, Cellectis, 8 rue de la Croix Jarry, Paris 75013, France. philippe.duchateau@cellectis.com.|Research and Development department, Cellectis, 8 rue de la Croix Jarry, Paris 75013, France. philippe.duchateau@cellectis.com.', 'Georgia|Georgia|France|France|France', 7, 'Artificial Intelligence|Computer Simulation|DNA|High-Throughput Screening Assays|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-15-191', '24934562', 'Meganucleases are important tools for genome engineering, providing an efficient way to generate DNA double-strand breaks at specific loci of interest. Numerous experimental efforts, ranging from in vivo selection to in silico modeling, have been made to re-engineer meganucleases to target relevant DNA sequences.'),
(96162, 2014, 'bmc', 'Online GESS: prediction of miRNA-like off-target effects in large-scale RNAi screen data by seed region analysis', 'Yilmazel, Bahar|Hu, Yanhui|Sigoillot, Frederic|Smith, Jennifer A|Shamu, Caroline E|Perrimon, Norbert|Mohr, Stephanie E', 'Research and Development department, Cellectis, 8 rue de la Croix Jarry, Paris 75013, France. philippe.duchateau@cellectis.com.|Research and Development department, Cellectis, 8 rue de la Croix Jarry, Paris 75013, France. philippe.duchateau@cellectis.com.|Research and Development department, Cellectis, 8 rue de la Croix Jarry, Paris 75013, France. philippe.duchateau@cellectis.com.|Research and Development department, Cellectis, 8 rue de la Croix Jarry, Paris 75013, France. philippe.duchateau@cellectis.com.|Research and Development department, Cellectis, 8 rue de la Croix Jarry, Paris 75013, France. philippe.duchateau@cellectis.com.|Research and Development department, Cellectis, 8 rue de la Croix Jarry, Paris 75013, France. philippe.duchateau@cellectis.com.|Drosophila RNAi Screening Center, Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA. stephanie_mohr@hms.harvard.edu.', 'France|France|France|France|France|France|United States', 24, 'Animals|Drosophila melanogaster|High-Throughput Nucleotide Sequencing|MicroRNAs|RNA Interference|RNA, Small Interfering|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-15-192', '24934636', 'RNA interference (RNAi) is an effective and important tool used to study gene function. For large-scale screens, RNAi is used to systematically down-regulate genes of interest and analyze their roles in a biological process. However, RNAi is associated with off-target effects (OTEs), including microRNA (miRNA)-like OTEs. The contribution of reagent-specific OTEs to RNAi screen data sets can be significant. In addition, the post-screen validation process is time and labor intensive. Thus, the availability of robust approaches to identify candidate off-targeted transcripts would be beneficial.'),
(96163, 2014, 'bmc', 'Phenotype prediction based on genome-wide DNA methylation data', 'Wilhelm, Thomas', 'Theoretical Systems Biology, Institute of Food Research, Norwich Research Park, Norwich NR4 7UA, UK. Thomas.wilhelm@ifr.ac.uk.', 'United Kingdom', 15, 'CpG Islands|DNA Methylation|Female|Genome, Human|Humans|Papillomaviridae|Papillomavirus Infections|Phenotype|Principal Component Analysis|Uterine Cervical Neoplasms', 'Journal Article', '10.1186/1471-2105-15-193', '24934728', 'DNA methylation (DNAm) has important regulatory roles in many biological processes and diseases. It is the only epigenetic mark with a clear mechanism of mitotic inheritance and the only one easily available on a genome scale. Aberrant cytosine-phosphate-guanine (CpG) methylation has been discussed in the context of disease aetiology, especially cancer. CpG hypermethylation of promoter regions is often associated with silencing of tumour suppressor genes and hypomethylation with activation of oncogenes.Supervised principal component analysis (SPCA) is a popular machine learning method. However, in a recent application to phenotype prediction from DNAm data SPCA was inferior to the specific method EVORA.'),
(96164, 2014, 'bmc', 'Identification of putative pathogenic SNPs implied in schizophrenia-associated miRNAs', 'Sun, Xiaohan|Zhang, Junying', 'Theoretical Systems Biology, Institute of Food Research, Norwich Research Park, Norwich NR4 7UA, UK. Thomas.wilhelm@ifr.ac.uk.|School of Computer Science and Technology, Xidian University, Xian 710071, P, R, China. jyzhang@mail.xidian.edu.cn.', 'United Kingdom|China', 5, 'Base Sequence|Humans|MicroRNAs|Molecular Sequence Data|Nucleic Acid Conformation|Polymorphism, Single Nucleotide|Schizophrenia', 'Journal Article', '10.1186/1471-2105-15-194', '24934851', 'Schizophrenia is a severe brain disorder, and SNPs (Single nucleotide polymorphism) in schizophrenia-associated miRNAs are believed to be one of the important reasons for dysregulation which might contribute to the altered expression of genes and ultimately result in the disease. Identification of causal SNPs in associated miRNAs may have certain significance in understanding the mechanism of schizophrenia.'),
(96165, 2014, 'bmc', 'Quantitative group testing-based overlapping pool sequencing to identify rare variant carriers', 'Cao, Chang-Chang|Li, Cheng|Sun, Xiao', 'School of Computer Science and Technology, Xidian University, Xian 710071, P, R, China. jyzhang@mail.xidian.edu.cn.|School of Computer Science and Technology, Xidian University, Xian 710071, P, R, China. jyzhang@mail.xidian.edu.cn.|State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China. xsun@seu.edu.cn.', 'China|China|China', 4, 'Algorithms|Base Sequence|Bayes Theorem|Computer Simulation|Escherichia coli|Genetic Variation|Genome-Wide Association Study|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-15-195', '24934981', 'Genome-wide association studies have revealed that rare variants are responsible for a large portion of the heritability of some complex human diseases. This highlights the increasing importance of detecting and screening for rare variants. Although the massively parallel sequencing technologies have greatly reduced the cost of DNA sequencing, the identification of rare variant carriers by large-scale re-sequencing remains prohibitively expensive because of the huge challenge of constructing libraries for thousands of samples. Recently, several studies have reported that techniques from group testing theory and compressed sensing could help identify rare variant carriers in large-scale samples with few pooled sequencing experiments and a dramatically reduced cost.'),
(96166, 2014, 'bmc', 'Structure- and context-based analysis of the GxGYxYP family reveals a new putative class of glycoside hydrolase', 'Rigden, Daniel J|Eberhardt, Ruth Y|Gilbert, Harry J|Xu, Qingping|Chang, Yuanyuan|Godzik, Adam', 'Institute of Integrative Biology, University of Liverpool, Liverpool, UK. drigden@liv.ac.uk.|Institute of Integrative Biology, University of Liverpool, Liverpool, UK. drigden@liv.ac.uk.|Institute of Integrative Biology, University of Liverpool, Liverpool, UK. drigden@liv.ac.uk.|Institute of Integrative Biology, University of Liverpool, Liverpool, UK. drigden@liv.ac.uk.|Institute of Integrative Biology, University of Liverpool, Liverpool, UK. drigden@liv.ac.uk.|Institute of Integrative Biology, University of Liverpool, Liverpool, UK. drigden@liv.ac.uk.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 6, 'Bacteroides|Biocatalysis|Glycoside Hydrolases|Models, Molecular|Phylogeny|Protein Structure, Tertiary|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-15-196', '24938123', 'Gut microbiome metagenomics has revealed many protein families and domains found largely or exclusively in that environment. Proteins containing the GxGYxYP domain are over-represented in the gut microbiota, and are found in Polysaccharide Utilization Loci in the gut symbiont Bacteroides thetaiotaomicron, suggesting their involvement in polysaccharide metabolism, but little else is known of the function of this domain.'),
(96167, 2014, 'bmc', 'KVFinder: steered identification of protein cavities as a PyMOL plugin', 'Oliveira, Saulo H P|Ferraz, Felipe A N|Honorato, Rodrigo V|Xavier-Neto, José|Sobreira, Tiago J P|de Oliveira, Paulo S L', 'Institute of Integrative Biology, University of Liverpool, Liverpool, UK. drigden@liv.ac.uk.|Institute of Integrative Biology, University of Liverpool, Liverpool, UK. drigden@liv.ac.uk.|Institute of Integrative Biology, University of Liverpool, Liverpool, UK. drigden@liv.ac.uk.|Institute of Integrative Biology, University of Liverpool, Liverpool, UK. drigden@liv.ac.uk.|Institute of Integrative Biology, University of Liverpool, Liverpool, UK. drigden@liv.ac.uk.|National Laboratory of Biosciences, P,O, Box 6192, CEP 13083-970 Campinas, SP, Brazil. paulo.oliveira@lnbio.cnpem.br.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|Brazil', 65, 'Algorithms|Binding Sites|Computational Biology|Ligands|Models, Molecular|Protein Binding|Protein Structure, Tertiary|Proteins|Software', 'Journal Article', '10.1186/1471-2105-15-197', '24938294', 'The characterization of protein binding sites is a major challenge in computational biology. Proteins interact with a wide variety of molecules and understanding of such complex interactions is essential to gain deeper knowledge of protein function. Shape complementarity is known to be important in determining protein-ligand interactions. Furthermore, these protein structural features have been shown to be useful in assisting medicinal chemists during lead discovery and optimization.'),
(96168, 2014, 'bmc', 'CIRCUS: a package for Circos display of structural genome variations from paired-end and mate-pair sequencing data', 'Naquin, Delphine|dAubenton-Carafa, Yves|Thermes, Claude|Silvain, Maud', 'Plateforme Intégrée IMAGIF - CNRS, Avenue de la Terrasse, Gif sur Yvette 91198, France. delphine.naquin@cgm.cnrs-gif.fr.|Plateforme Intégrée IMAGIF - CNRS, Avenue de la Terrasse, Gif sur Yvette 91198, France. delphine.naquin@cgm.cnrs-gif.fr.|Plateforme Intégrée IMAGIF - CNRS, Avenue de la Terrasse, Gif sur Yvette 91198, France. delphine.naquin@cgm.cnrs-gif.fr.|Plateforme Intégrée IMAGIF - CNRS, Avenue de la Terrasse, Gif sur Yvette 91198, France. delphine.naquin@cgm.cnrs-gif.fr.', 'France|France|France|France', 18, 'Genome|Genomics|High-Throughput Nucleotide Sequencing|Software Design', 'Journal Article', '10.1186/1471-2105-15-198', '24938393', 'Detection of large genomic rearrangements, such as large indels, duplications or translocations is now commonly achieved by next generation sequencing (NGS) approaches. Recently, several tools have been developed to analyze NGS data but the resulting files are difficult to interpret without an additional visualization step. Circos (Genome Res, 19:1639-1645, 2009), a Perl script, is a powerful visualization software that requires setting up numerous configuration files with a large number of parameters to handle. R packages like RCircos (BMC Bioinformatics, 14:244, 2013) or ggbio (Genome Biol, 13:R77, 2012) provide functions to display genomic data as circular Circos-like plots. However, these tools are very general and lack the functions needed to filter, format and adjust specific input genomic data.'),
(96169, 2014, 'bmc', 'Non-specific filtering of beta-distributed data', 'Wang, Xinhui|Laird, Peter W|Hinoue, Toshinori|Groshen, Susan|Siegmund, Kimberly D', 'Plateforme Intégrée IMAGIF - CNRS, Avenue de la Terrasse, Gif sur Yvette 91198, France. delphine.naquin@cgm.cnrs-gif.fr.|Plateforme Intégrée IMAGIF - CNRS, Avenue de la Terrasse, Gif sur Yvette 91198, France. delphine.naquin@cgm.cnrs-gif.fr.|Plateforme Intégrée IMAGIF - CNRS, Avenue de la Terrasse, Gif sur Yvette 91198, France. delphine.naquin@cgm.cnrs-gif.fr.|Plateforme Intégrée IMAGIF - CNRS, Avenue de la Terrasse, Gif sur Yvette 91198, France. delphine.naquin@cgm.cnrs-gif.fr.|Department of Preventive Medicine, USC Keck School of Medicine, University of Southern California, 2001 N Soto Street, Suite 202W, Los Angeles 90089-9239 California, USA. kims@usc.edu.', 'France|France|France|France|United States', 9, 'Computational Biology|CpG Islands|DNA Methylation|Humans|Neoplasms|Phenotype|Promoter Regions, Genetic|Statistical Distributions', 'Journal Article', '10.1186/1471-2105-15-199', '24943962', 'Non-specific feature selection is a dimension reduction procedure performed prior to cluster analysis of high dimensional molecular data. Not all measured features are expected to show biological variation, so only the most varying are selected for analysis. In DNA methylation studies, DNA methylation is measured as a proportion, bounded between 0 and 1, with variance a function of the mean. Filtering on standard deviation biases the selection of probes to those with mean values near 0.5. We explore the effect this has on clustering, and develop alternate filter methods that utilize a variance stabilizing transformation for Beta distributed data and do not share this bias.'),
(96170, 2014, 'bmc', 'Detecting protein complexes in protein interaction networks using a ranking algorithm with a refined merging procedure', 'Hanna, Eileen Marie|Zaki, Nazar', 'College of Information Technology, United Arab Emirates University (UAEU, Al Ain 17551, United Arab Emirates. eileen.hanna@uaeu.ac.ae.|College of Information Technology, United Arab Emirates University (UAEU, Al Ain 17551, United Arab Emirates. eileen.hanna@uaeu.ac.ae.', 'United Arab Emirates|United Arab Emirates', 15, 'Algorithms|Cluster Analysis|Humans|Internet|Protein Interaction Mapping|Protein Interaction Maps|Proteins', 'Journal Article', '10.1186/1471-2105-15-204', '24944073', 'Developing suitable methods for the identification of protein complexes remains an active research area. It is important since it allows better understanding of cellular functions as well as malfunctions and it consequently leads to producing more effective cures for diseases. In this context, various computational approaches were introduced to complement high-throughput experimental methods which typically involve large datasets, are expensive in terms of time and cost, and are usually subject to spurious interactions.'),
(96171, 2014, 'bmc', 'A model-based information sharing protocol for profile Hidden Markov Models used for HIV-1 recombination detection', 'Bulla, Ingo|Schultz, Anne-Kathrin|Chesneau, Christophe|Mark, Tanya|Serea, Florin', 'Institut für Mathematik und Informatik, Universität Greifswald, Walther-Rathenau-Straße 47, 17487 Greifswald, Germany. ingobulla@gmail.com.|Institut für Mathematik und Informatik, Universität Greifswald, Walther-Rathenau-Straße 47, 17487 Greifswald, Germany. ingobulla@gmail.com.|Institut für Mathematik und Informatik, Universität Greifswald, Walther-Rathenau-Straße 47, 17487 Greifswald, Germany. ingobulla@gmail.com.|Institut für Mathematik und Informatik, Universität Greifswald, Walther-Rathenau-Straße 47, 17487 Greifswald, Germany. ingobulla@gmail.com.|Institut für Mathematik und Informatik, Universität Greifswald, Walther-Rathenau-Straße 47, 17487 Greifswald, Germany. ingobulla@gmail.com.', 'Germany|Germany|Germany|Germany|Germany', 3, 'Algorithms|Base Sequence|Computational Biology|Genetic Variation|HIV-1|Host-Pathogen Interactions|Humans|Immunity|Markov Chains|Models, Biological|Models, Statistical|Recombination, Genetic', 'Journal Article', '10.1186/1471-2105-15-205', '24946781', 'In many applications, a family of nucleotide or protein sequences classified into several subfamilies has to be modeled. Profile Hidden Markov Models (pHMMs) are widely used for this task, modeling each subfamily separately by one pHMM. However, a major drawback of this approach is the difficulty of dealing with subfamilies composed of very few sequences. One of the most crucial bioinformatical tasks affected by the problem of small-size subfamilies is the subtyping of human immunodeficiency virus type 1 (HIV-1) sequences, i.e., HIV-1 subtypes for which only a small number of sequences is known.'),
(96172, 2014, 'bmc', 'A unifying model of genome evolution under parsimony', 'Paten, Benedict|Zerbino, Daniel R|Hickey, Glenn|Haussler, David', 'University of California, Santa Cruz, 1156 High St, 95064 Santa Cruz, USA. benedict@soe.ucsc.edu.|University of California, Santa Cruz, 1156 High St, 95064 Santa Cruz, USA. benedict@soe.ucsc.edu.|University of California, Santa Cruz, 1156 High St, 95064 Santa Cruz, USA. benedict@soe.ucsc.edu.|University of California, Santa Cruz, 1156 High St, 95064 Santa Cruz, USA. benedict@soe.ucsc.edu.', 'United States|United States|United States|United States', 5, 'Algorithms|Evolution, Molecular|Genome|Likelihood Functions|Models, Genetic', 'Journal Article', '10.1186/1471-2105-15-206', '24946830', 'Parsimony and maximum likelihood methods of phylogenetic tree estimation and parsimony methods for genome rearrangements are central to the study of genome evolution yet to date they have largely been pursued in isolation.'),
(96173, 2014, 'bmc', 'Automated peptide mapping and protein-topographical annotation of proteomics data', 'Videm, Pavankumar|Gunasekaran, Deepika|Schröder, Bernd|Mayer, Bettina|Biniossek, Martin L|Schilling, Oliver', 'University of California, Santa Cruz, 1156 High St, 95064 Santa Cruz, USA. benedict@soe.ucsc.edu.|University of California, Santa Cruz, 1156 High St, 95064 Santa Cruz, USA. benedict@soe.ucsc.edu.|University of California, Santa Cruz, 1156 High St, 95064 Santa Cruz, USA. benedict@soe.ucsc.edu.|University of California, Santa Cruz, 1156 High St, 95064 Santa Cruz, USA. benedict@soe.ucsc.edu.|University of California, Santa Cruz, 1156 High St, 95064 Santa Cruz, USA. benedict@soe.ucsc.edu.|Institute of Molecular Medicine and Cell Research, University of Freiburg, D-79104 Freiburg, Germany. oliver.schilling@mol-med.uni-freiburg.de.', 'United States|United States|United States|United States|United States|Germany', 6, 'Automation, Laboratory|Humans|Molecular Sequence Annotation|Peptide Mapping|Proteins|Proteomics', 'Journal Article', '10.1186/1471-2105-15-207', '24946880', 'In quantitative proteomics, peptide mapping is a valuable approach to combine positional quantitative information with topographical and domain information of proteins. Quantitative proteomic analysis of cell surface shedding is an exemplary application area of this approach.'),
(96174, 2014, 'bmc', 'Stronger findings from mass spectral data through multi-peak modeling', 'Suvitaival, Tommi|Rogers, Simon|Kaski, Samuel', 'Institute of Molecular Medicine and Cell Research, University of Freiburg, D-79104 Freiburg, Germany. oliver.schilling@mol-med.uni-freiburg.de.|Institute of Molecular Medicine and Cell Research, University of Freiburg, D-79104 Freiburg, Germany. oliver.schilling@mol-med.uni-freiburg.de.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, 00076 Espoo, Finland. samuel.kaski@aalto.fi.', 'Germany|Germany|Finland', 5, 'Bayes Theorem|Cluster Analysis|Lipids|Mass Spectrometry|Metabolomics', 'Journal Article', '10.1186/1471-2105-15-208', '24947013', 'Mass spectrometry-based metabolomic analysis depends upon the identification of spectral peaks by their mass and retention time. Statistical analysis that follows the identification currently relies on one main peak of each compound. However, a compound present in the sample typically produces several spectral peaks due to its isotopic properties and the ionization process of the mass spectrometer device. In this work, we investigate the extent to which these additional peaks can be used to increase the statistical strength of differential analysis.'),
(96175, 2014, 'bmc', 'Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patterns', 'Li, Rongjian|Zhang, Wenlu|Ji, Shuiwang', 'Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, 00076 Espoo, Finland. samuel.kaski@aalto.fi.|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, 00076 Espoo, Finland. samuel.kaski@aalto.fi.|Department of Computer Science, Old Dominion University, 23529 Norfolk, VA, USA. sji@cs.odu.edu.', 'Finland|Finland|United States', 5, 'Animals|Automation, Laboratory|Brain|Gene Expression|Gene Expression Profiling|In Situ Hybridization|Mice|Organ Specificity', 'Journal Article', '10.1186/1471-2105-15-209', '24947138', 'Differential gene expression patterns in cells of the mammalian brain result in the morphological, connectional, and functional diversity of cells. A wide variety of studies have shown that certain genes are expressed only in specific cell-types. Analysis of cell-type-specific gene expression patterns can provide insights into the relationship between genes, connectivity, brain regions, and cell-types. However, automated methods for identifying cell-type-specific genes are lacking to date.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96176, 2014, 'bmc', 'Exploiting large-scale drug-protein interaction information for computational drug repurposing', 'Liu, Ruifeng|Singh, Narender|Tawa, Gregory J|Wallqvist, Anders|Reifman, Jaques', 'Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U,S, Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA. RLiu@bhsai.org.|Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U,S, Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA. RLiu@bhsai.org.|Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U,S, Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA. RLiu@bhsai.org.|Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U,S, Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA. RLiu@bhsai.org.|Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U,S, Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA. RLiu@bhsai.org.', 'United States|United States|United States|United States|United States', 12, 'Bayes Theorem|Drug Approval|Drug Interactions|Drug Repositioning|Hypertension|Proteins|United States', 'Journal Article', '10.1186/1471-2105-15-210', '24950817', 'Despite increased investment in pharmaceutical research and development, fewer and fewer new drugs are entering the marketplace. This has prompted studies in repurposing existing drugs for use against diseases with unmet medical needs. A popular approach is to develop a classification model based on drugs with and without a desired therapeutic effect. For this approach to be statistically sound, it requires a large number of drugs in both classes. However, given few or no approved drugs for the diseases of highest medical urgency and interest, different strategies need to be investigated.'),
(96177, 2014, 'bmc', 'SSPACE-LongRead: scaffolding bacterial draft genomes using long read sequence information', 'Boetzer, Marten|Pirovano, Walter', 'Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U,S, Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA. RLiu@bhsai.org.|BaseClear B,V,, Genome analysis and technology department, Einsteinweg 5, Leiden 2333 CC, The Netherlands. walter.pirovano@baseclear.com.', 'United States|Netherlands', 0, 'Gene Library|Genome, Bacterial|High-Throughput Nucleotide Sequencing|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-15-211', '24950923', 'The recent introduction of the Pacific Biosciences RS single molecule sequencing technology has opened new doors to scaffolding genome assemblies in a cost-effective manner. The long read sequence information is promised to enhance the quality of incomplete and inaccurate draft assemblies constructed from Next Generation Sequencing (NGS) data.'),
(96178, 2014, 'bmc', 'CicArMiSatDB: the chickpea microsatellite database', 'Doddamani, Dadakhalandar|Katta, Mohan A V S K|Khan, Aamir W|Agarwal, Gaurav|Shah, Trushar M|Varshney, Rajeev K', 'BaseClear B,V,, Genome analysis and technology department, Einsteinweg 5, Leiden 2333 CC, The Netherlands. walter.pirovano@baseclear.com.|BaseClear B,V,, Genome analysis and technology department, Einsteinweg 5, Leiden 2333 CC, The Netherlands. walter.pirovano@baseclear.com.|BaseClear B,V,, Genome analysis and technology department, Einsteinweg 5, Leiden 2333 CC, The Netherlands. walter.pirovano@baseclear.com.|BaseClear B,V,, Genome analysis and technology department, Einsteinweg 5, Leiden 2333 CC, The Netherlands. walter.pirovano@baseclear.com.|BaseClear B,V,, Genome analysis and technology department, Einsteinweg 5, Leiden 2333 CC, The Netherlands. walter.pirovano@baseclear.com.|International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502324, India. r.k.varshney@cgiar.org.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|India', 18, 'Base Sequence|Breeding|Chromosome Mapping|Cicer|Databases, Genetic|Genomics|Internet|Microsatellite Repeats|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-15-212', '24952649', 'Chickpea (Cicer arietinum) is a widely grown legume crop in tropical, sub-tropical and temperate regions. Molecular breeding approaches seem to be essential for enhancing crop productivity in chickpea. Until recently, limited numbers of molecular markers were available in the case of chickpea for use in molecular breeding. However, the recent advances in genomics facilitated the development of large scale markers especially SSRs (simple sequence repeats), the markers of choice in any breeding program. Availability of genome sequence very recently opens new avenues for accelerating molecular breeding approaches for chickpea improvement.'),
(96179, 2014, 'bmc', 'Homology-based prediction of interactions between proteins using Averaged One-Dependence Estimators', 'Murakami, Yoichi|Mizuguchi, Kenji', 'Bioinformatics Project, National Institute of Biomedical Innovation, 7-6-8 Saito-Asagi, Ibaraki, Osaka 567-0085, Japan. yoichi@ecei.tohoku.ac.jp.|Bioinformatics Project, National Institute of Biomedical Innovation, 7-6-8 Saito-Asagi, Ibaraki, Osaka 567-0085, Japan. yoichi@ecei.tohoku.ac.jp.', 'Japan|Japan', 0, 'Amino Acid Sequence|Computational Biology|Humans|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/1471-2105-15-213', '24953126', 'Identification of protein-protein interactions (PPIs) is essential for a better understanding of biological processes, pathways and functions. However, experimental identification of the complete set of PPIs in a cell/organism (an interactome) is still a difficult task. To circumvent limitations of current high-throughput experimental techniques, it is necessary to develop high-performance computational methods for predicting PPIs.'),
(96180, 2014, 'bmc', 'e!DAL--a framework to store, share and publish research data', 'Arend, Daniel|Lange, Matthias|Chen, Jinbo|Colmsee, Christian|Flemming, Steffen|Hecht, Denny|Scholz, Uwe', 'Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstr, 3, 06466 Stadt Seeland, Germany. arendd@ipk-gatersleben.de.|Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstr, 3, 06466 Stadt Seeland, Germany. arendd@ipk-gatersleben.de.|Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstr, 3, 06466 Stadt Seeland, Germany. arendd@ipk-gatersleben.de.|Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstr, 3, 06466 Stadt Seeland, Germany. arendd@ipk-gatersleben.de.|Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstr, 3, 06466 Stadt Seeland, Germany. arendd@ipk-gatersleben.de.|Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstr, 3, 06466 Stadt Seeland, Germany. arendd@ipk-gatersleben.de.|Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstr, 3, 06466 Stadt Seeland, Germany. arendd@ipk-gatersleben.de.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 40, 'Databases, Factual|Information Dissemination|Software', 'Journal Article', '10.1186/1471-2105-15-214', '24958009', 'The life-science community faces a major challenge in handling big data, highlighting the need for high quality infrastructures capable of sharing and publishing research data. Data preservation, analysis, and publication are the three pillars in the big data life cycle. The infrastructures currently available for managing and publishing data are often designed to meet domain-specific or project-specific requirements, resulting in the repeated development of proprietary solutions and lower quality data publication and preservation overall.'),
(96181, 2014, 'bmc', 'Using beta-binomial regression for high-precision differential methylation analysis in multifactor whole-genome bisulfite sequencing experiments', 'Dolzhenko, Egor|Smith, Andrew D', 'Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstr, 3, 06466 Stadt Seeland, Germany. arendd@ipk-gatersleben.de.|Molecular and Computational Biology Section, Division of Biological Sciences, University of Southern California, Los Angeles, California, USA. andrewds@usc.edu.', 'Germany|United States', 0, 'CpG Islands|DNA Methylation|Genomics|Models, Statistical|Nucleotides|Regression Analysis|Sequence Analysis, DNA|Sulfites', 'Journal Article', '10.1186/1471-2105-15-215', '24962134', 'Whole-genome bisulfite sequencing currently provides the highest-precision view of the epigenome, with quantitative information about populations of cells down to single nucleotide resolution. Several studies have demonstrated the value of this precision: meaningful features that correlate strongly with biological functions can be found associated with only a few CpG sites. Understanding the role of DNA methylation, and more broadly the role of DNA accessibility, requires that methylation differences between populations of cells are identified with extreme precision and in complex experimental designs.'),
(96182, 2014, 'bmc', 'Heterogeneous computing architecture for fast detection of SNP-SNP interactions', 'Sluga, Davor|Curk, Tomaz|Zupan, Blaz|Lotric, Uros', 'Molecular and Computational Biology Section, Division of Biological Sciences, University of Southern California, Los Angeles, California, USA. andrewds@usc.edu.|Molecular and Computational Biology Section, Division of Biological Sciences, University of Southern California, Los Angeles, California, USA. andrewds@usc.edu.|Molecular and Computational Biology Section, Division of Biological Sciences, University of Southern California, Los Angeles, California, USA. andrewds@usc.edu.|Faculty of Computer and Information Science, University of Ljubljana, Trzaska 25, SI 1000 Ljubljana, SI, Slovenia. uros.lotric@fri.uni-lj.si.', 'United States|United States|United States|Slovenia', 0, 'Algorithms|Computational Biology|Computer Graphics|Genome-Wide Association Study|High-Throughput Nucleotide Sequencing|Internet|Polymorphism, Single Nucleotide|Software|Time Factors', 'Journal Article', '10.1186/1471-2105-15-216', '24964802', 'The extent of data in a typical genome-wide association study (GWAS) poses considerable computational challenges to software tools for gene-gene interaction discovery. Exhaustive evaluation of all interactions among hundreds of thousands to millions of single nucleotide polymorphisms (SNPs) may require weeks or even months of computation. Massively parallel hardware within a modern Graphic Processing Unit (GPU) and Many Integrated Core (MIC) coprocessors can shorten the run time considerably. While the utility of GPU-based implementations in bioinformatics has been well studied, MIC architecture has been introduced only recently and may provide a number of comparative advantages that have yet to be explored and tested.'),
(96183, 2014, 'bmc', 'A semi-local neighborhood-based framework for probabilistic cell lineage tracing', 'Santella, Anthony|Du, Zhuo|Bao, Zhirong', 'Faculty of Computer and Information Science, University of Ljubljana, Trzaska 25, SI 1000 Ljubljana, SI, Slovenia. uros.lotric@fri.uni-lj.si.|Faculty of Computer and Information Science, University of Ljubljana, Trzaska 25, SI 1000 Ljubljana, SI, Slovenia. uros.lotric@fri.uni-lj.si.|Developmental Biology, Sloan-Kettering Institute, 1275 York Avenue, New York, New York 10065, USA. baoz@mskcc.org.', 'Slovenia|Slovenia|United States', 24, 'Animals|Bayes Theorem|Caenorhabditis elegans|Cell Lineage|Probability', 'Journal Article', '10.1186/1471-2105-15-217', '24964866', 'Advances in fluorescence labeling and imaging have made it possible to acquire in vivo records of complex biological processes. Analysis has lagged behind acquisition in part because of the difficulty and computational expense of accurate cell tracking. In vivo analysis requires, at minimum, tracking hundreds of cells over hundreds of time points in complex three dimensional environments. We address this challenge with a computational framework capable of efficiently and accurately tracing entire cell lineages.'),
(96184, 2014, 'bmc', 'SHERPA: an image segmentation and outline feature extraction tool for diatoms and other objects', 'Kloster, Michael|Kauer, Gerhard|Beszteri, Bánk', 'AWI: Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany. michael.kloster@awi.de.|AWI: Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany. michael.kloster@awi.de.|AWI: Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany. michael.kloster@awi.de.', 'Germany|Germany|Germany', 23, 'Algorithms|Automation|Diatoms|Image Processing, Computer-Assisted|Microscopy|Software', 'Journal Article', '10.1186/1471-2105-15-218', '24964954', 'Light microscopic analysis of diatom frustules is widely used both in basic and applied research, notably taxonomy, morphometrics, water quality monitoring and paleo-environmental studies. In these applications, usually large numbers of frustules need to be identified and/or measured. Although there is a need for automation in these applications, and image processing and analysis methods supporting these tasks have previously been developed, they did not become widespread in diatom analysis. While methodological reports for a wide variety of methods for image segmentation, diatom identification and feature extraction are available, no single implementation combining a subset of these into a readily applicable workflow accessible to diatomists exists.'),
(96185, 2014, 'bmc', 'Ycasd - a tool for capturing and scaling data from graphical representations', 'Gross, Arnd|Schirm, Sibylle|Scholz, Markus', 'Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107 Leipzig, Germany. arnd.gross@imise.uni-leipzig.de.|Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107 Leipzig, Germany. arnd.gross@imise.uni-leipzig.de.|Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107 Leipzig, Germany. arnd.gross@imise.uni-leipzig.de.', 'Germany|Germany|Germany', 0, 'Computational Biology|Computer Graphics|Humans|Models, Biological|Software|Statistics as Topic|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-15-219', '24965054', 'Mathematical modelling of biological processes often requires a large variety of different data sets for parameter estimation and validation. It is common practice that clinical data are not available in raw formats but are provided as graphical representations. Hence, in order to include these data into environments used for model simulations and statistical analyses, it is necessary to extract them from their presentations in the literature. For this purpose, we developed the freely available open source tool ycasd. After establishing a coordinate system by simple axes definitions, it supports convenient retrieval of data points from arbitrary figures.'),
(96186, 2014, 'bmc', 'Exploring community structure in biological networks with random graphs', 'Sah, Pratha|Singh, Lisa O|Clauset, Aaron|Bansal, Shweta', 'Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107 Leipzig, Germany. arnd.gross@imise.uni-leipzig.de.|Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107 Leipzig, Germany. arnd.gross@imise.uni-leipzig.de.|Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107 Leipzig, Germany. arnd.gross@imise.uni-leipzig.de.|Department of Biology, Georgetown University, 20057 Washington DC, USA. sb753@georgetown.edu.', 'Germany|Germany|Germany|United States', 0, 'Algorithms|Cluster Analysis|Computational Biology|Computer Graphics|Humans|Models, Biological', 'Journal Article', '10.1186/1471-2105-15-220', '24965130', 'Community structure is ubiquitous in biological networks. There has been an increased interest in unraveling the community structure of biological systems as it may provide important insights into a systems functional components and the impact of local structures on dynamics at a global scale. Choosing an appropriate community detection algorithm to identify the community structure in an empirical network can be difficult, however, as the many algorithms available are based on a variety of cost functions and are difficult to validate. Even when community structure is identified in an empirical system, disentangling the effect of community structure from other network properties such as clustering coefficient and assortativity can be a challenge.'),
(96187, 2014, 'bmc', 'Steady state analysis of Boolean molecular network models via model reduction and computational algebra', 'Veliz-Cuba, Alan|Aguilar, Boris|Hinkelmann, Franziska|Laubenbacher, Reinhard', 'Department of Mathematics, University of Houston, 651 PGH Building, Houston TX, USA. alanavc@math.uh.edu.|Department of Mathematics, University of Houston, 651 PGH Building, Houston TX, USA. alanavc@math.uh.edu.|Department of Mathematics, University of Houston, 651 PGH Building, Houston TX, USA. alanavc@math.uh.edu.|Department of Mathematics, University of Houston, 651 PGH Building, Houston TX, USA. alanavc@math.uh.edu.', 'United States|United States|United States|United States', 0, 'Algorithms|Computational Biology|Models, Biological|Software', 'Journal Article', '10.1186/1471-2105-15-221', '24965213', 'A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the network. The dimension of published models is growing to over 100, so that efficient methods for steady state determination are essential. Several methods have been proposed for large networks, some of them heuristic. While these methods represent a substantial improvement in scalability over exhaustive enumeration, the problem for large networks is still unsolved in general.'),
(96188, 2014, 'bmc', 'Identification and phylogenetic analyses of VASt, an uncharacterized protein domain associated with lipid-binding domains in Eukaryotes', 'Khafif, Mehdi|Cottret, Ludovic|Balagué, Claudine|Raffaele, Sylvain', 'Department of Mathematics, University of Houston, 651 PGH Building, Houston TX, USA. alanavc@math.uh.edu.|Department of Mathematics, University of Houston, 651 PGH Building, Houston TX, USA. alanavc@math.uh.edu.|Department of Mathematics, University of Houston, 651 PGH Building, Houston TX, USA. alanavc@math.uh.edu.|INRA, Laboratoire des Interactions Plantes-Microorganismes (LIPM), UMR441, 24 Chemin de Borde Rouge - Auzeville, CS52627, F31326 Castanet Tolosan Cedex, France. Sylvain.raffaele@toulouse.inra.fr.', 'United States|United States|United States|France', 0, 'Amino Acid Sequence|Animals|Conserved Sequence|Eukaryota|Genome|Humans|Lipid Metabolism|Lipids|Models, Molecular|Molecular Sequence Data|Phylogeny|Protein Structure, Tertiary|Proteins|Sequence Alignment|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-15-222', '24965341', 'Several regulators of programmed cell death (PCD) in plants encode proteins with putative lipid-binding domains. Among them, VAD1 is a regulator of PCD propagation harboring a GRAM putative lipid-binding domain. However the function of VAD1 at the subcellular level is unknown and the domain architecture of VAD1 has not been analyzed in details.'),
(96189, 2014, 'bmc', 'A comparative study of the SVM and K-nn machine learning algorithms for the diagnosis of respiratory pathologies using pulmonary acoustic signals', 'Palaniappan, Rajkumar|Sundaraj, Kenneth|Sundaraj, Sebastian', 'AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.', 'Malaysia|Malaysia|Malaysia', 60, 'Acoustics|Algorithms|Analysis of Variance|Diagnosis, Differential|Humans|Lung|Respiratory Tract Diseases|Signal Processing, Computer-Assisted|Support Vector Machine', 'Comparative Study', '10.1186/1471-2105-15-223', '24970564', 'Pulmonary acoustic parameters extracted from recorded respiratory sounds provide valuable information for the detection of respiratory pathologies. The automated analysis of pulmonary acoustic signals can serve as a differential diagnosis tool for medical professionals, a learning tool for medical students, and a self-management tool for patients. In this context, we intend to evaluate and compare the performance of the support vector machine (SVM) and K-nearest neighbour (K-nn) classifiers in diagnosis respiratory pathologies using respiratory sounds from R.A.L.E database.'),
(96190, 2014, 'bmc', 'MAP-RSeq: Mayo Analysis Pipeline for RNA sequencing', 'Kalari, Krishna R|Nair, Asha A|Bhavsar, Jaysheel D|OBrien, Daniel R|Davila, Jaime I|Bockol, Matthew A|Nie, Jinfu|Tang, Xiaojia|Baheti, Saurabh|Doughty, Jay B|Middha, Sumit|Sicotte, Hugues|Thompson, Aubrey E|Asmann, Yan W|Kocher, Jean-Pierre A', 'AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|AI-Rehab Research Group, Kampus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia. prkmect@gmail.com.|Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. kocher.jeanpierre@mayo.edu.', 'Malaysia|Malaysia|Malaysia|Malaysia|Malaysia|Malaysia|Malaysia|Malaysia|Malaysia|Malaysia|Malaysia|M', 0, 'Base Sequence|Exons|Gene Expression Profiling|Genomics|Health Facilities|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-15-224', '24972667', 'Although the costs of next generation sequencing technology have decreased over the past years, there is still a lack of simple-to-use applications, for a comprehensive analysis of RNA sequencing data. There is no one-stop shop for transcriptomic genomics. We have developed MAP-RSeq, a comprehensive computational workflow that can be used for obtaining genomic features from transcriptomic sequencing data, for any genome.'),
(96191, 2014, 'bmc', 'Efficiently gap-filling reaction networks', 'Latendresse, Mario', 'Bioinformatics Research Group/Artificial Intelligence Center, SRI International, 333 Ravenswood Ave, Menlo Park 94025, USA. latendre@ai.sri.com.', 'United States', 0, 'Algorithms|Escherichia coli|Genomics|Metabolic Flux Analysis|Metabolic Networks and Pathways|Models, Biological|Yeasts', 'Journal Article', '10.1186/1471-2105-15-225', '24972703', 'Flux Balance Analysis (FBA) is a genome-scale computational technique for modeling the steady-state fluxes of an organisms reaction network. When the organisms reaction network needs to be completed to obtain growth using FBA, without relying on the genome, the completion process is called reaction gap-filling. Currently, computational techniques used to gap-fill a reaction network compute the minimum set of reactions using Mixed-Integer Linear Programming (MILP). Depending on the number of candidate reactions used to complete the model, MILP can be computationally demanding.'),
(96192, 2014, 'bmc', 'Meta-analysis based on weighted ordered P-values for genomic data with heterogeneity', 'Li, Yihan|Ghosh, Debashis', 'Bioinformatics Research Group/Artificial Intelligence Center, SRI International, 333 Ravenswood Ave, Menlo Park 94025, USA. latendre@ai.sri.com.|Department of Statistics, Pennsylvania State University, University Park, Pennsylvania 16802, USA. ghoshd@psu.edu.', 'United States|United States', 7, 'Biostatistics|Genomics|Humans|Meta-Analysis as Topic|Probability', 'Journal Article', '10.1186/1471-2105-15-226', '24972803', 'Meta-analysis has become increasingly popular in recent years, especially in genomic data analysis, due to the fast growth of available data and studies that target the same questions. Many methods have been developed, including classical ones such as Fishers combined probability test and Stouffers Z-test. However, not all meta-analyses have the same goal in mind. Some aim at combining information to find signals in at least one of the studies, while others hope to find more consistent signals across the studies. While many classical meta-analysis methods are developed with the former goal in mind, the latter goal has much more practicality for genomic data analysis.'),
(96193, 2014, 'bmc', 'A universal genomic coordinate translator for comparative genomics', 'Zamani, Neda|Sundström, Görel|Meadows, Jennifer R S|Höppner, Marc P|Dainat, Jacques|Lantz, Henrik|Haas, Brian J|Grabherr, Manfred G', 'Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden. neda.zamani@imbim.uu.se.|Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden. neda.zamani@imbim.uu.se.|Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden. neda.zamani@imbim.uu.se.|Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden. neda.zamani@imbim.uu.se.|Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden. neda.zamani@imbim.uu.se.|Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden. neda.zamani@imbim.uu.se.|Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden. neda.zamani@imbim.uu.se.|Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden. neda.zamani@imbim.uu.se.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 3, 'Animals|Chromosome Mapping|Drosophila melanogaster|Evolution, Molecular|Genome|Genomics|Humans|Mice|Molecular Sequence Annotation|Rats|Software|Synteny|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-15-227', '24976580', 'Genomic duplications constitute major events in the evolution of species, allowing paralogous copies of genes to take on fine-tuned biological roles. Unambiguously identifying the orthology relationship between copies across multiple genomes can be resolved by synteny, i.e. the conserved order of genomic sequences. However, a comprehensive analysis of duplication events and their contributions to evolution would require all-to-all genome alignments, which increases at N2 with the number of available genomes, N.'),
(96194, 2014, 'bmc', 'Estimating causal effects with a non-paranormal method for the design of efficient intervention experiments', 'Teramoto, Reiji|Saito, Chiaki|Funahashi, Shin-ichi', 'Department for Research, Forerunner Pharma Research, Co,, Ltd, Yokohama, Japan. teramoto@forerunner-pharma.co.jp.|Department for Research, Forerunner Pharma Research, Co,, Ltd, Yokohama, Japan. teramoto@forerunner-pharma.co.jp.|Department for Research, Forerunner Pharma Research, Co,, Ltd, Yokohama, Japan. teramoto@forerunner-pharma.co.jp.', 'Japan|Japan|Japan', 0, 'Adipocytes, Brown|Adipocytes, White|Algorithms|Animals|Arabidopsis|Data Interpretation, Statistical|Gene Knockdown Techniques|Genetic Techniques|High-Throughput Nucleotide Sequencing|Mice|Normal Distribution|Phenotype|Regression Analysis', 'Journal Article', '10.1186/1471-2105-15-228', '24980787', 'Knockdown or overexpression of genes is widely used to identify genes that play important roles in many aspects of cellular functions and phenotypes. Because next-generation sequencing generates high-throughput data that allow us to detect genes, it is important to identify genes that drive functional and phenotypic changes of cells. However, conventional methods rely heavily on the assumption of normality and they often give incorrect results when the assumption is not true. To relax the Gaussian assumption in causal inference, we introduce the non-paranormal method to test conditional independence in the PC-algorithm. Then, we present the non-paranormal intervention-calculus when the directed acyclic graph (DAG) is absent (NPN-IDA), which incorporates the cumulative nature of effects through a cascaded pathway via causal inference for ranking causal genes against a phenotype with the non-paranormal method for estimating DAGs.'),
(96195, 2014, 'bmc', 'SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models', 'Reid, Ian|OToole, Nicholas|Zabaneh, Omar|Nourzadeh, Reza|Dahdouli, Mahmoud|Abdellateef, Mostafa|Gordon, Paul M K|Soh, Jung|Butler, Gregory|Sensen, Christoph W|Tsang, Adrian', 'Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke St, W, Montreal, QC H4B 1R6, Canada. ian.reid@concordia.ca.|Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke St, W, Montreal, QC H4B 1R6, Canada. ian.reid@concordia.ca.|Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke St, W, Montreal, QC H4B 1R6, Canada. ian.reid@concordia.ca.|Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke St, W, Montreal, QC H4B 1R6, Canada. ian.reid@concordia.ca.|Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke St, W, Montreal, QC H4B 1R6, Canada. ian.reid@concordia.ca.|Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke St, W, Montreal, QC H4B 1R6, Canada. ian.reid@concordia.ca.|Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke St, W, Montreal, QC H4B 1R6, Canada. ian.reid@concordia.ca.|Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke St, W, Montreal, QC H4B 1R6, Canada. ian.reid@concordia.ca.|Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke St, W, Montreal, QC H4B 1R6, Canada. ian.reid@concordia.ca.|Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke St, W, Montreal, QC H4B 1R6, Canada. ian.reid@concordia.ca.|Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke St, W, Montreal, QC H4B 1R6, Canada. ian.reid@concordia.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Genes, Fungal|Genome, Fungal|Genomics|Markov Chains|Models, Genetic|Molecular Sequence Annotation|RNA, Fungal|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-15-229', '24980894', 'Locating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them.'),
(96196, 2014, 'bmc', 'Osiris: accessible and reproducible phylogenetic and phylogenomic analyses within the Galaxy workflow management system', 'Oakley, Todd H|Alexandrou, Markos A|Ngo, Roger|Pankey, M Sabrina|Churchill, Celia K C|Chen, William|Lopker, Karl B', 'Ecology, Evolution, and Marine Biology, University of California-Santa Barbara, Santa Barbara, CA 93106, USA. oakley@lifesci.ucsb.edu.|Ecology, Evolution, and Marine Biology, University of California-Santa Barbara, Santa Barbara, CA 93106, USA. oakley@lifesci.ucsb.edu.|Ecology, Evolution, and Marine Biology, University of California-Santa Barbara, Santa Barbara, CA 93106, USA. oakley@lifesci.ucsb.edu.|Ecology, Evolution, and Marine Biology, University of California-Santa Barbara, Santa Barbara, CA 93106, USA. oakley@lifesci.ucsb.edu.|Ecology, Evolution, and Marine Biology, University of California-Santa Barbara, Santa Barbara, CA 93106, USA. oakley@lifesci.ucsb.edu.|Ecology, Evolution, and Marine Biology, University of California-Santa Barbara, Santa Barbara, CA 93106, USA. oakley@lifesci.ucsb.edu.|Ecology, Evolution, and Marine Biology, University of California-Santa Barbara, Santa Barbara, CA 93106, USA. oakley@lifesci.ucsb.edu.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Computational Biology|Phylogeny|Sequence Alignment|Software|User-Computer Interface|Workflow', 'Journal Article', '10.1186/1471-2105-15-230', '24990571', 'Phylogenetic tools and tree-thinking approaches increasingly permeate all biological research. At the same time, phylogenetic data sets are expanding at breakneck pace, facilitated by increasingly economical sequencing technologies. Therefore, there is an urgent need for accessible, modular, and sharable tools for phylogenetic analysis.'),
(96197, 2014, 'bmc', 'A spatial simulation approach to account for protein structure when identifying non-random somatic mutations', 'Ryslik, Gregory A|Cheng, Yuwei|Cheung, Kei-Hoi|Bjornson, Robert D|Zelterman, Daniel|Modis, Yorgo|Zhao, Hongyu', 'Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. gregory.ryslik@yale.edu.', 'United States|United States|United States|United States|United States|United States|United States', 15, 'Algorithms|Cluster Analysis|Computational Biology|Databases, Protein|Genes, Neoplasm|Humans|Mutation|Neoplasms|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1186/1471-2105-15-231', '24990767', 'Current research suggests that a small set of driver mutations are responsible for tumorigenesis while a larger body of passenger mutations occur in the tumor but do not progress the disease. Due to recent pharmacological successes in treating cancers caused by driver mutations, a variety of methodologies that attempt to identify such mutations have been developed. Based on the hypothesis that driver mutations tend to cluster in key regions of the protein, the development of cluster identification algorithms has become critical.'),
(96198, 2014, 'bmc', 'On the potential of models for location and scale for genome-wide DNA methylation data', 'Wahl, Simone|Fenske, Nora|Zeilinger, Sonja|Suhre, Karsten|Gieger, Christian|Waldenberger, Melanie|Grallert, Harald|Schmid, Matthias', 'Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Case-Control Studies|CpG Islands|DNA Methylation|Epigenesis, Genetic|Genomics|Humans|Models, Statistical|Neoplasms|Normal Distribution', 'Journal Article', '10.1186/1471-2105-15-232', '24994026', 'With the help of epigenome-wide association studies (EWAS), increasing knowledge on the role of epigenetic mechanisms such as DNA methylation in disease processes is obtained. In addition, EWAS aid the understanding of behavioral and environmental effects on DNA methylation. In terms of statistical analysis, specific challenges arise from the characteristics of methylation data. First, methylation xcexb2-values represent proportions with skewed and heteroscedastic distributions. Thus, traditional modeling strategies assuming a normally distributed response might not be appropriate. Second, recent evidence suggests that not only mean differences but also variability in site-specific DNA methylation associates with diseases, including cancer. The purpose of this study was to compare different modeling strategies for methylation data in terms of model performance and performance of downstream hypothesis tests. Specifically, we used the generalized additive models for location, scale and shape (GAMLSS) framework to compare beta regression with Gaussian regression on raw, binary logit and arcsine square root transformed methylation data, with and without modeling a covariate effect on the scale parameter.'),
(96199, 2014, 'bmc', 'BorreliaBase: a phylogeny-centered browser of Borrelia genomes', 'Di, Lia|Pagan, Pedro E|Packer, Daniel|Martin, Che L|Akther, Saymon|Ramrattan, Girish|Mongodin, Emmanuel F|Fraser, Claire M|Schutzer, Steven E|Luft, Benjamin J|Casjens, Sherwood R|Qiu, Wei-Gang', 'Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Research Unit of Molecular Epidemiology, Helmholtz Zentrum Mxc3xbcnchen - German Research Center for Environmental Health, Ingolstxc3xa4dter Landstrasse 1, 85764 Neuherberg, Germany. simone.wahl@helmholtz-muenchen.de.|Department of Biological Sciences, Hunter College, The City University of New York, 10065 New York, NY, USA. weigang@genectr.hunter.cuny.edu.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|United States', 24, 'Borrelia|Databases, Genetic|Evolution, Molecular|Genome, Bacterial|Humans|Phylogeny|Sequence Alignment|User-Computer Interface|Web Browser', 'Journal Article', '10.1186/1471-2105-15-233', '24994456', 'The bacterial genus Borrelia (phylum Spirochaetes) consists of two groups of pathogens represented respectively by B. burgdorferi, the agent of Lyme borreliosis, and B. hermsii, the agent of tick-borne relapsing fever. The number of publicly available Borrelia genomic sequences is growing rapidly with the discovery and sequencing of Borrelia strains worldwide. There is however a lack of dedicated online databases to facilitate comparative analyses of Borrelia genomes.'),
(96200, 2014, 'bmc', 'Building blocks for automated elucidation of metabolites: natural product-likeness for candidate ranking', 'Jayaseelan, Kalai Vanii|Steinbeck, Christoph', 'Cheminformatics and Metabolism, European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. kalai@ebi.ac.uk.|Cheminformatics and Metabolism, European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. kalai@ebi.ac.uk.', 'United Kingdom|United Kingdom', 0, 'Algorithms|Automation|Biological Products|Biostatistics|Magnetic Resonance Spectroscopy|Mass Spectrometry|Metabolomics', 'Journal Article', '10.1186/1471-2105-15-234', '24996690', 'In metabolomics experiments, spectral fingerprints of metabolites with no known structural identity are detected routinely. Computer-assisted structure elucidation (CASE) has been used to determine the structural identities of unknown compounds. It is generally accepted that a single 1D NMR spectrum or mass spectrum is usually not sufficient to establish the identity of a hitherto unknown compound. When a suite of spectra from 1D and 2D NMR experiments supplemented with a molecular formula are available, the successful elucidation of the chemical structure for candidates with up to 30 heavy atoms has been reported previously by one of the authors. In high-throughput metabolomics, usually 1D NMR or mass spectrometry experiments alone are conducted for rapid analysis of samples. This method subsequently requires that the spectral patterns are analyzed automatically to quickly identify known and unknown structures. In this study, we investigated whether additional existing knowledge, such as the fact that the unknown compound is a natural product, can be used to improve the ranking of the correct structure in the result list after the structure elucidation process.'),
(96201, 2014, 'bmc', 'Addressing the unmet need for visualizing conditional random fields in biological data', 'Ray, William C|Wolock, Samuel L|Callahan, Nicholas W|Dong, Min|Li, Q Quinn|Liang, Chun|Magliery, Thomas J|Bartlett, Christopher W', 'Nationwide Childrens Hospital, 575 Childrens Crossroad, 43215 Columbus, OH, USA. ray.29@osu.edu.|Nationwide Childrens Hospital, 575 Childrens Crossroad, 43215 Columbus, OH, USA. ray.29@osu.edu.|Nationwide Childrens Hospital, 575 Childrens Crossroad, 43215 Columbus, OH, USA. ray.29@osu.edu.|Nationwide Childrens Hospital, 575 Childrens Crossroad, 43215 Columbus, OH, USA. ray.29@osu.edu.|Nationwide Childrens Hospital, 575 Childrens Crossroad, 43215 Columbus, OH, USA. ray.29@osu.edu.|Nationwide Childrens Hospital, 575 Childrens Crossroad, 43215 Columbus, OH, USA. ray.29@osu.edu.|Nationwide Childrens Hospital, 575 Childrens Crossroad, 43215 Columbus, OH, USA. ray.29@osu.edu.|Nationwide Childrens Hospital, 575 Childrens Crossroad, 43215 Columbus, OH, USA. ray.29@osu.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Internet|Models, Statistical|Software', 'Journal Article', '10.1186/1471-2105-15-202', '25000815', 'The biological world is replete with phenomena that appear to be ideally modeled and analyzed by one archetypal statistical framework - the Graphical Probabilistic Model (GPM). The structure of GPMs is a uniquely good match for biological problems that range from aligning sequences to modeling the genome-to-phenome relationship. The fundamental questions that GPMs address involve making decisions based on a complex web of interacting factors. Unfortunately, while GPMs ideally fit many questions in biology, they are not an easy solution to apply. Building a GPM is not a simple task for an end user. Moreover, applying GPMs is also impeded by the insidious fact that the complex web of interacting factors inherent to a problem might be easy to define and also intractable to compute upon.');
