ArticleNucleic acids research2005
oPOSSUM: identification of over-represented transcription factor binding sites in co-expressed genes.
Article in Nucleic acids research, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 218 papers, 2 of them syntheses that pooled it.
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Who cites it
218 citing papers in PubMed, 2 syntheses or guidelines pooled it, 378 citations in OpenAlex.
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158 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Targeted transcript profiling studies can identify sets of co-expressed genes; however, identification of the underlying functional mechanism(s) is a significant challenge. Established methods for the analysis of gene annotations, particularly those based on the Gene Ontology, can identify functional linkages between genes. Similar methods for the identification of over-represented transcription factor binding sites (TFBSs) have been successful in yeast, but extension to human genomics has largely proved ineffective. Creation of a system for the efficient identification of common regulatory mechanisms in a subset of co-expressed human genes promises to break a roadblock in functional genomics research. We have developed an integrated system that searches for evidence of co-regulation by one or more transcription factors (TFs). oPOSSUM combines a pre-computed database of conserved TFBSs in human and mouse promoters with statistical methods for identification of sites over-represented in a set of co-expressed genes. The algorithm successfully identified mediating TFs in control sets of tissue-specific genes and in sets of co-expressed genes from three transcript profiling studies. Simulation studies indicate that oPOSSUM produces few false positives using empirically defined thresholds and can tolerate up to 50% noise in a set of co-expressed genes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.