Netmes: Assessing gene network inference algorithms by network-based measures

Gökmen Altay, Zeyneb Kurt, Matthias Dehmer, Frank Emmert-Streib

    Research output: Contribution to journalArticleScientificpeer-review

    Abstract

    Gene regulatory network inference (GRNI) algorithms are essential for efficiently utilizing large-scale microarray datasets to elucidate biochemical interactions among molecules in a cell. Recently, the combination of network-based error measures complemented with an ensemble approach became popular for assessing the inference performance of the GRNI algorithms. For this reason, we developed a software package to facilitate the usage of such metrics. In this paper, we present netmes, an R software package that allows the assessment of GRNI algorithms. The software package netmes is available from the R-Forge web site https://r-forge.r-project.org/projects/netmes/.

    Original languageEnglish
    JournalEvolutionary Bioinformatics
    Volume10
    DOIs
    Publication statusPublished - 7 Dec 2013
    Publication typeA1 Journal article-refereed

    Keywords

    • Gene regulatory networks
    • Global network-based measures
    • Local network-based measures
    • Metrics for assessing ensemble datasets
    • R package for the network-based measures

    ASJC Scopus subject areas

    • Ecology, Evolution, Behavior and Systematics
    • Computer Science Applications
    • Genetics

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