@article{Wang2010b,
abstract = {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.},
author = {Wang, Haiying and Zheng, Huiru and Azuaje, Francisco},
doi = {10.1093/bioinformatics/btq477},
issn = {1367-4811},
journal = {Bioinformatics (Oxford, England)},
keywords = {Algorithms,Biological Markers,Biological Markers: analysis,Computational Biology,Computational Biology: methods,Drug Discovery,SML-LIB-BIBLIO,lang:ENG},
mendeley-tags = {SML-LIB-BIBLIO,lang:ENG},
month = oct,
number = {20},
pages = {2643--4},
pmid = {20801912},
title = {{Ontology- and graph-based similarity assessment in biological networks.}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/20801912},
volume = {26},
year = {2010}
}