Evaluating topology-based metrics for GO term similarity measures

Jong Cheol Jeong, Xue Wen Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Defining semantic functional similarity measures provides effective means to validate protein function prediction methods and to retrieve biologically relevant information from big biological data. It also improves understanding of interrelationship between genes and gene products (GPs). Currently, one of the most commonly used tools for functionally annotating genes and GPs is the Gene Ontology (GO), which describes genes/GPs using a machine-readable language. To measure the semantic similarity between two GO terms, many studies that are based on GO topology have recently been reported. However, a comprehensive assessment and general guidelines for validating these methods are lacking. In this paper, we collect a large dataset to evaluate five often-used semantic similarity measure methods by estimating sequence similarity, phylogenetic profile similarity, and structural similarity. We further compare the measures in terms of their clustering performance using domains extracted from SCOP database. We describe some key aspects of these measure methods and discuss how the limitations may be addressed as well as some open problems.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
Pages43-48
Number of pages6
DOIs
StatePublished - 2013
Event2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013 - Shanghai, China
Duration: Dec 18 2013Dec 21 2013

Publication series

NameProceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013

Conference

Conference2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
Country/TerritoryChina
CityShanghai
Period12/18/1312/21/13

Keywords

  • gene ontology
  • gene products
  • semantic functional similarity

ASJC Scopus subject areas

  • Biomedical Engineering

Fingerprint

Dive into the research topics of 'Evaluating topology-based metrics for GO term similarity measures'. Together they form a unique fingerprint.

Cite this