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

  • Gökmen Altay*
  • , Zeyneb Kurt
  • , Matthias Dehmer
  • , Frank Emmert-Streib
  • *Corresponding author for this work
  • Bahcesehir University
  • Yildiz Technical University
  • UMIT-The Health and Life Sciences University
  • Queen's University Belfast

Research output: Contribution to journalArticlepeer-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
Externally publishedYes

Keywords

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

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