Ontology- and graph-based similarity assessment in biological networks

 


Haiying Wang1, Huiru Zheng1 and Francisco Azuaje2

1 Computer Science Research Institute, School of Computing and Mathematics, University of Ulster, UK. 

2Laboratory of Cardiovascular Research, Public Research Centre for Health (CRP-Sante), L-1150, Luxembourg.

contact email: francisco.azuaje@crp-sante.lu


Abstract

A standard systems-based approach to biomarker (or 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 we report an alternative analysis approach in which the networks are analyzed on a “semantic similarity” space. Such information is extracted from ontology-based functional annotations. We present SimTrek, a Cytoscape plugin for ontology-based similarity assessment of biological networks.

Downloads

  1. Supplementary Section: download here

  2. Software:

    New features in V1.2:

    New features in V1.3:


  3. A sample network studied in the paper: download here (right click)

  4. User Guidelines:(V1.1, V1.2)

Citation

If you use this software in your research please cite:

Wang H, Zheng H, Azuaje F (2010) Ontology- and graph-based similarity assessment in biological networks, Bioinformatics.