Netmes: Assessing Gene Network Inference Algorithms by Network-Based Measures

Altay G., Kurt Z., Dehmer M., Emmert-Streib F.

EVOLUTIONARY BIOINFORMATICS, vol.10, pp.1-9, 2014 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 10
  • Publication Date: 2014
  • Doi Number: 10.4137/ebo.s13481
  • Journal Name: EVOLUTIONARY BIOINFORMATICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1-9
  • Yıldız Technical University Affiliated: Yes

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/.