An improved method for functional similarity analysis of genes based on Gene Ontology. Issue 4 (December 2016)
- Record Type:
- Journal Article
- Title:
- An improved method for functional similarity analysis of genes based on Gene Ontology. Issue 4 (December 2016)
- Main Title:
- An improved method for functional similarity analysis of genes based on Gene Ontology
- Authors:
- Tian, Zhen
Wang, Chunyu
Guo, Maozu
Liu, Xiaoyan
Teng, Zhixia - Abstract:
- Abstract Background Measures of gene functional similarity are essential tools for gene clustering, gene function prediction, evaluation of protein-protein interaction, disease gene prioritization and other applications. In recent years, many gene functional similarity methods have been proposed based on the semantic similarity of GO terms. However, these leading approaches may make errorprone judgments especially when they measure the specificity of GO terms as well as the IC of a term set. Therefore, how to estimate the gene functional similarity reliably is still a challenging problem. Results We propose WIS, an effective method to measure the gene functional similarity. First of all, WIS computes the IC of a term by employing its depth, the number of its ancestors as well as the topology of its descendants in the GO graph. Secondly, WIS calculates the IC of a term set by means of considering the weighted inherited semantics of terms. Finally, WIS estimates the gene functional similarity based on the IC overlap ratio of term sets. WIS is superior to some other representative measures on the experiments of functional classification of genes in a biological pathway, collaborative evaluation of GO-based semantic similarity measures, protein-protein interaction prediction and correlation with gene expression. Further analysis suggests that WIS takes fully into account the specificity of terms and the weighted inherited semantics of terms between GO terms. Conclusions TheAbstract Background Measures of gene functional similarity are essential tools for gene clustering, gene function prediction, evaluation of protein-protein interaction, disease gene prioritization and other applications. In recent years, many gene functional similarity methods have been proposed based on the semantic similarity of GO terms. However, these leading approaches may make errorprone judgments especially when they measure the specificity of GO terms as well as the IC of a term set. Therefore, how to estimate the gene functional similarity reliably is still a challenging problem. Results We propose WIS, an effective method to measure the gene functional similarity. First of all, WIS computes the IC of a term by employing its depth, the number of its ancestors as well as the topology of its descendants in the GO graph. Secondly, WIS calculates the IC of a term set by means of considering the weighted inherited semantics of terms. Finally, WIS estimates the gene functional similarity based on the IC overlap ratio of term sets. WIS is superior to some other representative measures on the experiments of functional classification of genes in a biological pathway, collaborative evaluation of GO-based semantic similarity measures, protein-protein interaction prediction and correlation with gene expression. Further analysis suggests that WIS takes fully into account the specificity of terms and the weighted inherited semantics of terms between GO terms. Conclusions The proposed WIS method is an effective and reliable way to compare gene function. The web service of WIS is freely available athttp://nclab.hit.edu.cn/WIS/ . … (more)
- Is Part Of:
- BMC systems biology. Volume 10:Issue 4(2016)
- Journal:
- BMC systems biology
- Issue:
- Volume 10:Issue 4(2016)
- Issue Display:
- Volume 10, Issue 4 (2016)
- Year:
- 2016
- Volume:
- 10
- Issue:
- 4
- Issue Sort Value:
- 2016-0010-0004-0000
- Page Start:
- 465
- Page End:
- 484
- Publication Date:
- 2016-12
- Subjects:
- Gene Ontology -- Specificity of terms -- Weighted inherited semantics -- Gene functional similarity
Biological systems -- Periodicals
Biology -- Research -- Periodicals
Cell physiology -- Periodicals
Genes -- Analysis -- Periodicals
571 - Journal URLs:
- http://www.biomedcentral.com/bmcsystbiol/ ↗
http://link.springer.com/ ↗ - DOI:
- 10.1186/s12918-016-0359-z ↗
- Languages:
- English
- ISSNs:
- 1752-0509
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 10954.xml