Detection of Gene Orthology from Gene Co-expression and Protein Interaction Networks

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2010 May 5

PMID 20438654

Citations 11

Authors

Fadi Towfic

Susan Vanderplas

Casey A Oliver

Oliver Couture

Christopher K Tuggle

M Heather West Greenlee

Vasant Honavar

Affiliations

Soon will be listed here.

Abstract

Background: Ortholog detection methods present a powerful approach for finding genes that participate in similar biological processes across different organisms, extending our understanding of interactions between genes across different pathways, and understanding the evolution of gene families.

Results: We exploit features derived from the alignment of protein-protein interaction networks and gene-coexpression networks to reconstruct KEGG orthologs for Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository and Mus musculus and Homo sapiens and Sus scrofa gene coexpression networks extracted from NCBI's Gene Expression Omnibus using the decision tree, Naive-Bayes and Support Vector Machine classification algorithms.

Conclusions: The performance of our classifiers in reconstructing KEGG orthologs is compared against a basic reciprocal BLAST hit approach. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit.

Citing Articles

Artificial intelligence in cancer target identification and drug discovery.

You Y, Lai X, Pan Y, Zheng H, Vera J, Liu S Signal Transduct Target Ther. 2022; 7(1):156.

PMID: 35538061 PMC: 9090746. DOI: 10.1038/s41392-022-00994-0.

Comparative Analyses of Gene Co-expression Networks: Implementations and Applications in the Study of Evolution.

Ovens K, Eames B, McQuillan I Front Genet. 2021; 12:695399.

PMID: 34484293 PMC: 8414652. DOI: 10.3389/fgene.2021.695399.

Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers.

Galpert D, Fernandez A, Herrera F, Antunes A, Molina-Ruiz R, Aguero-Chapin G BMC Bioinformatics. 2018; 19(1):166.

PMID: 29724166 PMC: 5934817. DOI: 10.1186/s12859-018-2148-8.

Meta-analysis of Liver and Heart Transcriptomic Data for Functional Annotation Transfer in Mammalian Orthologs.

Reyes P, Michoel T, Joshi A, Devailly G Comput Struct Biotechnol J. 2017; 15:425-432.

PMID: 29187960 PMC: 5691612. DOI: 10.1016/j.csbj.2017.08.002.

Inferring Orthologs: Open Questions and Perspectives.

Tekaia F Genomics Insights. 2016; 9:17-28.

PMID: 26966373 PMC: 4778853. DOI: 10.4137/GEI.S37925.

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