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

Research output: Contribution to journalArticleScientificpeer-review


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


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/.


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