A standard systems-based approach to biomarker and drug target discovery consists of placing putative biomarkers in the context of a network of biological interactions, followed by different guilt-by-association analyses. The latter is typically done based on network structural features. Here, an alternative analysis approach in which the networks are analyzed on a semantic similarity space is reported. Such information is extracted from ontology-based functional annotations. We present SimTrek, a Cytoscape plugin for ontology-based similarity assessment in biological networks.