Netmes: Assessing Gene Network Inference Algorithms by Network-Based Measures - Altay, Gokmen; Kurt, Zeyneb; Dehmer, Matthias; Emmert-Streib, Frank (SAGE PUBLICATIONS LTD, 2014)
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/.
Keywords: global network-based measures; local network-based measures; metrics for assessing ensemble datasets; R package for the network-based measures; gene regulatory networks; TRANSCRIPTIONAL REGULATORY NETWORK; MOTIFS; Evolutionary Biology; Mathematical & Computational Biology