ArticleGene regulation and systems biology2010
Identifying a Transcription Factor's Regulatory Targets from its Binding Targets.
Article in Gene regulation and systems biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- Functional redundancy of transcription factors explains why most binding targets of a transcription factor are not affected when the transcription factor is knocked out.BMC systems biology · 2015Article
- Integrative analysis of C. elegans modENCODE ChIP-seq data sets to infer gene regulatory interactions.Genome research · 2013Article
- Roles of the developmental regulator unc-62/Homothorax in limiting longevity in Caenorhabditis elegans.PLoS genetics · 2013Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
ChIP-chip data, which shows binding of transcription factors (TFs) to promoter regions in vivo, are widely used by biologists to identify the regulatory targets of TFs. However, the binding of a TF to a gene does not necessarily imply regulation. Thus, it is important to develop computational methods which can extract a TF's regulatory targets from its binding targets. We developed a method, called REgulatory Targets Extraction Algorithm (RETEA), which uses partial correlation analysis on gene expression data to extract a TF's regulatory targets from its binding targets inferred from ChIP-chip data. We applied RETEA to yeast cell cycle microarray data and identified the plausible regulatory targets of eleven known cell cycle TFs. We validated our predictions by checking the enrichments for cell cycle-regulated genes, common cellular processes and common molecular functions. Finally, we showed that RETEA performs better than three published methods (MA-Network, TRIA and Garten et al's method).
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