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 language | English |
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Journal | Evolutionary Bioinformatics |
Volume | 10 |
DOIs | |
Publication status | Published - 7 Dec 2013 |
Publication type | A1 Journal article-refereed |
Keywords
- Gene regulatory networks
- Global network-based measures
- Local network-based measures
- Metrics for assessing ensemble datasets
- R package for the network-based measures
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Computer Science Applications
- Genetics