YeastNet v3: A public database of data-specific and integrated functional gene networks for Saccharomyces cerevisiae

Hanhae Kim, Junha Shin, Eiru Kim, Hyojin Kim, Sohyun Hwang, Jung Eun Shim, Insuk Lee

Research output: Contribution to journalArticle

45 Citations (Scopus)

Abstract

Saccharomyces cerevisiae, i.e. baker's yeast, is a widely studied model organism in eukaryote genetics because of its simple protocols for genetic manipulation and phenotype profiling. The high abundance of publicly available data that has been generated through diverse 'omics' approaches has led to the use of yeast for many systems biology studies, including large-scale gene network modeling to better understand the molecular basis of the cellular phenotype. We have previously developed a genome-scale gene network for yeast, YeastNet v2, which has been used for various genetics and systems biology studies. Here, we present an updated version, YeastNet v3 (available at http://www.inetbio.org/yeastnet/), that significantly improves the prediction of gene-phenotype associations. The extended genome in YeastNet v3 covers up to 5818 genes (∼99% of the coding genome) wired by 362 512 functional links. YeastNet v3 provides a new web interface to run the tools for network-guided hypothesis generations. YeastNet v3 also provides edge information for all data-specific networks (∼2 million functional links) as well as the integrated networks. Therefore, users can construct alternative versions of the integrated network by applying their own data integration algorithm to the same data-specific links.

Original languageEnglish
Pages (from-to)D731-D736
JournalNucleic acids research
Volume42
Issue numberD1
DOIs
Publication statusPublished - 2014 Jan 1

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All Science Journal Classification (ASJC) codes

  • Genetics

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