Measuring semantic similarities by combining gene ontology annotations and gene co-function networks

Peng, Jiajie; Uygun, Sahra; Kim, Taehyong; Wang, Yadong; Rhee, Seung Y.; Chen, Jin

doi:10.1186/s12859-015-0474-7

Title: Measuring semantic similarities by combining gene ontology annotations and gene co-function networks

Abstract

Background: Gene Ontology (GO) has been used widely to study functional relationships between genes. The current semantic similarity measures rely only on GO annotations and GO structure. This limits the power of GO-based similarity because of the limited proportion of genes that are annotated to GO in most organisms. Results: We introduce a novel approach called NETSIM (network-based similarity measure) that incorporates information from gene co-function networks in addition to using the GO structure and annotations. Using metabolic reaction maps of yeast, Arabidopsis, and human, we demonstrate that NETSIM can improve the accuracy of GO term similarities. We also demonstrate that NETSIM works well even for genomes with sparser gene annotation data. We applied NETSIM on large Arabidopsis gene families such as cytochrome P450 monooxygenases to group the members functionally and show that this grouping could facilitate functional characterization of genes in these families. Conclusions: Using NETSIM as an example, we demonstrated that the performance of a semantic similarity measure could be significantly improved after incorporating genome-specific information. NETSIM incorporates both GO annotations and gene co-function network data as a priori knowledge in the model. Therefore, functional similarities of GO terms that are not explicitly encoded in GO but aremore »« less

Authors:

Peng, Jiajie ^[1]; Uygun, Sahra ^[2]; Kim, Taehyong ^[3]; Wang, Yadong ^[4]; Rhee, Seung Y. ^[3]; Chen, Jin ^[5]

Harbin Institute of Technology, Harbin (China); Michigan State Univ., East Lansing, MI (United States)
Michigan State Univ., East Lansing, MI (United States)
Carnegie Institution for Science, Stanford, CA (United States)
Harbin Institute of Technology, Harbin (China)
Michigan State University, East Lansing, MI (United States)

Publication Date:: 2015-02-14

Research Org.:: Michigan State Univ., East Lansing, MI (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

OSTI Identifier:: 1194164

Grant/Contract Number:: FG02-91ER20021

Resource Type:: Accepted Manuscript

Journal Name:: BMC Bioinformatics

Additional Journal Information:: Journal Volume: 16; Journal Issue: 1; Journal ID: ISSN 1471-2105

Publisher:: BioMed Central

Country of Publication:: United States

Language:: English

Subject:: 59 BASIC BIOLOGICAL SCIENCES; co-function network; gene ontology; semantic similarity; gene function annotation

Citation Formats


                    Peng, Jiajie, Uygun, Sahra, Kim, Taehyong, Wang, Yadong, Rhee, Seung Y., and Chen, Jin. Measuring semantic similarities by combining gene ontology annotations and gene co-function networks.  United States: N. p., 2015. 
        Web.  doi:10.1186/s12859-015-0474-7.

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                    Peng, Jiajie, Uygun, Sahra, Kim, Taehyong, Wang, Yadong, Rhee, Seung Y., & Chen, Jin. Measuring semantic similarities by combining gene ontology annotations and gene co-function networks.  United States.  doi:https://doi.org/10.1186/s12859-015-0474-7

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                    Peng, Jiajie, Uygun, Sahra, Kim, Taehyong, Wang, Yadong, Rhee, Seung Y., and Chen, Jin. Sat .  
        "Measuring semantic similarities by combining gene ontology annotations and gene co-function networks".  United States.  doi:https://doi.org/10.1186/s12859-015-0474-7.  https://www.osti.gov/servlets/purl/1194164.

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@article{osti_1194164,

  title        = {Measuring semantic similarities by combining gene ontology annotations and gene co-function networks},

  author       = {Peng, Jiajie and Uygun, Sahra and Kim, Taehyong and Wang, Yadong and Rhee, Seung Y. and Chen, Jin},

  abstractNote = {Background: Gene Ontology (GO) has been used widely to study functional relationships between genes. The current semantic similarity measures rely only on GO annotations and GO structure. This limits the power of GO-based similarity because of the limited proportion of genes that are annotated to GO in most organisms. Results: We introduce a novel approach called NETSIM (network-based similarity measure) that incorporates information from gene co-function networks in addition to using the GO structure and annotations. Using metabolic reaction maps of yeast, Arabidopsis, and human, we demonstrate that NETSIM can improve the accuracy of GO term similarities. We also demonstrate that NETSIM works well even for genomes with sparser gene annotation data. We applied NETSIM on large Arabidopsis gene families such as cytochrome P450 monooxygenases to group the members functionally and show that this grouping could facilitate functional characterization of genes in these families. Conclusions: Using NETSIM as an example, we demonstrated that the performance of a semantic similarity measure could be significantly improved after incorporating genome-specific information. NETSIM incorporates both GO annotations and gene co-function network data as a priori knowledge in the model. Therefore, functional similarities of GO terms that are not explicitly encoded in GO but are relevant in a taxon-specific manner become measurable when GO annotations are limited.},

  doi          = {10.1186/s12859-015-0474-7},

  journal      = {BMC Bioinformatics},

  number       = 1,

  volume       = 16,

  place        = {United States},

  year         = {2015},

  month        = {2}

}

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DOI: https://doi.org/10.1186/s12859-015-0474-7

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Title: Measuring semantic similarities by combining gene ontology annotations and gene co-function networks

Abstract

Citation Formats

Gene Ontology: tool for the unification of biology journal, May 2000

Using GOstats to test gene lists for GO term association journal, November 2006

Evaluation of high-throughput functional categorization of human disease genes journal, January 2007

Predicting gene function through systematic analysis and quality assessment of high-throughput data journal, November 2004

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A categorization approach to automated ontological function annotation journal, June 2006

A new measure for functional similarity of gene products based on Gene Ontology journal, June 2006

A new method to measure the semantic similarity of GO terms journal, March 2007

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Semantic Similarity in Biomedical Ontologies journal, July 2009

The Gene Ontology Categorizer journal, July 2004

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An Improved, Bias-Reduced Probabilistic Functional Gene Network of Baker's Yeast, Saccharomyces cerevisiae journal, October 2007

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Use and misuse of the gene ontology annotations journal, May 2008

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The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases journal, November 2013

An integrated approach to characterize genetic interaction networks in yeast metabolism journal, May 2011

Diversification of P450 Genes During Land Plant Evolution journal, June 2010

Diverse Transcriptional Programs Associated with Environmental Stress and Hormones in the Arabidopsis Receptor-Like Kinase Gene Family journal, January 2009

PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors journal, October 2013

Microarray data analysis: from disarray to consolidation and consensus journal, January 2006

Total ancestry measure: quantifying the similarity in tree-like classification, with genomic applications journal, May 2007

Defining genetic interaction journal, February 2008

Towards revealing the functions of all genes in plants journal, April 2014

The MIPS mammalian protein-protein interaction database journal, November 2004

STRING v9.1: protein-protein interaction networks, with increased coverage and integration journal, November 2012

Arabidopsis Transcription Factors: Genome-Wide Comparative Analysis Among Eukaryotes journal, December 2000

Basic local alignment search tool journal, October 1990

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Creation of a Genome-Wide Metabolic Pathway Database for Populus trichocarpa Using a New Approach for Reconstruction and Curation of Metabolic Pathways for Plants journal, June 2010

Comparing partitions journal, December 1985

QuickGO: a web-based tool for Gene Ontology searching journal, September 2009

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Gene Ontology: tool for the unification of biology
journal, May 2000

Using GOstats to test gene lists for GO term association
journal, November 2006

Evaluation of high-throughput functional categorization of human disease genes
journal, January 2007

Predicting gene function through systematic analysis and quality assessment of high-throughput data
journal, November 2004

Globally predicting protein functions based on co-expressed protein–protein interaction networks and ontology taxonomy similarities
journal, April 2007

A categorization approach to automated ontological function annotation
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A new measure for functional similarity of gene products based on Gene Ontology
journal, June 2006

A new method to measure the semantic similarity of GO terms
journal, March 2007

Measuring gene functional similarity based on group-wise comparison of GO terms
journal, April 2013

Improving the Measurement of Semantic Similarity between Gene Ontology Terms and Gene Products: Insights from an Edge- and IC-Based Hybrid Method
journal, May 2013

Semantic Similarity in Biomedical Ontologies
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The Gene Ontology Categorizer
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Enhanced automated function prediction using distantly related sequences and contextual association by PFP
journal, June 2006

An Improved, Bias-Reduced Probabilistic Functional Gene Network of Baker's Yeast, Saccharomyces cerevisiae
journal, October 2007

Rational association of genes with traits using a genome-scale gene network for Arabidopsis thaliana
journal, January 2010

Prioritizing candidate disease genes by network-based boosting of genome-wide association data
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Use and misuse of the gene ontology annotations
journal, May 2008

The Arabidopsis Information Resource (TAIR): improved gene annotation and new tools
journal, December 2011

Saccharomyces Genome Database: the genomics resource of budding yeast
journal, November 2011

MetaCyc and AraCyc. Metabolic Pathway Databases for Plant Research
journal, May 2005

The Pathway Tools software
journal, July 2002

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases
journal, November 2013

An integrated approach to characterize genetic interaction networks in yeast metabolism
journal, May 2011

Diversification of P450 Genes During Land Plant Evolution
journal, June 2010

Diverse Transcriptional Programs Associated with Environmental Stress and Hormones in the Arabidopsis Receptor-Like Kinase Gene Family
journal, January 2009

PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors
journal, October 2013

Microarray data analysis: from disarray to consolidation and consensus
journal, January 2006

Total ancestry measure: quantifying the similarity in tree-like classification, with genomic applications
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Defining genetic interaction
journal, February 2008

Towards revealing the functions of all genes in plants
journal, April 2014

The MIPS mammalian protein-protein interaction database
journal, November 2004

STRING v9.1: protein-protein interaction networks, with increased coverage and integration
journal, November 2012

Arabidopsis Transcription Factors: Genome-Wide Comparative Analysis Among Eukaryotes
journal, December 2000

Basic local alignment search tool
journal, October 1990

Cytochrome P450 and Chemical Toxicology
journal, January 2008

Creation of a Genome-Wide Metabolic Pathway Database for Populus trichocarpa Using a New Approach for Reconstruction and Curation of Metabolic Pathways for Plants
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Constructing an integrated gene similarity network for the identification of disease genes
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