title: Ontology- and graph-based similarity assessment in biological networks.
abstract: CONCLUSIONS
  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.
  
  
  BACKGROUND
  http://rosalind.infj.ulst.ac.uk/SimTrek.html
  
  
  BACKGROUND
  francisco.azuaje@crp-sante.lu
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Computer Science Research Institute, School of Computing and Mathematics, University of Ulster.
authors.forename: Haiying
authors.initials: H
authors.lastname: Wang
authors.forename: Huiru
authors.initials: H
authors.lastname: Zheng
authors.forename: Francisco
authors.initials: F
authors.lastname: Azuaje
mesh_terms: D000465:Algorithms; D015415:Biomarkers / Q000032:analysis*; D019295:Computational Biology / Q000379:methods*; D055808:Drug Discovery
chemical_list: D015415:Biomarkers