Netmes: Assessing Gene Network Inference Algorithms by Network-Based Measures. (January 2014)

• Record Type: Journal Article
• Authors: Altay, Gökmen; Kurt, Zeyneb; Dehmer, Matthias; Emmert-Streib, Frank
• Is Part Of: Evolutionary bioinformatics online. Volume 10(2014)
• Publication Date: 2014-01
• Subjects: global network-based measures -- local network-based measures -- metrics for assessing ensemble datasets -- R package for the network-based measures -- gene regulatory networks; Bioinformatics -- Periodicals; Evolutionary computation -- Periodicals; Genetic programming (Computer science) -- Periodicals; Computational Biology; Evolution, Molecular; Bioinformatics; Electronic journals; Periodicals; Fulltext; Internet Resources; Periodicals; Periodicals; 576.8
• DOI: 10.4137/EBO.S13481
• Languages: English
• ISSNs: 1176-9343

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 sitehttps://r-forge.r-project.org/projects/netmes/ .