dorsal/arxiv
View SchemaComputational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrepresented upstream motifs
| Authors | Davide Cora', Ferdinando Di Cunto, Paolo Provero, Lorenzo Silengo, Michele Caselle |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0310040 |
| URL | https://arxiv.org/abs/q-bio/0310040 |
| Journal | BMC Bioinformatics. 2004 May 11;5(1):57 |
Abstract
BACKGROUND: Transcriptional regulation is a key mechanism in the functioning of the cell, and is mostly effected through transcription factors binding to specific recognition motifs located upstream of the coding region of the regulated gene. The computational identification of such motifs is made easier by the fact that they often appear several times in the upstream region of the regulated genes, so that the number of occurrences of relevant motifs is often significantly larger than expected by pure chance. RESULTS: To exploit this fact, we construct sets of genes characterized by the statistical overrepresentation of a certain motif in their upstream regions. Then we study the functional characterization of these sets by analyzing their annotation to Gene Ontology terms. For the sets showing a statistically significant specific functional characterization, we conjecture that the upstream motif characterizing the set is a binding site for a transcription factor involved in the regulation of the genes in the set. CONCLUSIONS: The method we propose is able to identify many known binding sites in S. cerevisiae and new candidate targets of regulation by known transcription factors. Its application to less well studied organisms is likely to be valuable in the exploration of their regulatory interaction network.
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"abstract": "BACKGROUND: Transcriptional regulation is a key mechanism in the functioning\nof the cell, and is mostly effected through transcription factors binding to\nspecific recognition motifs located upstream of the coding region of the\nregulated gene. The computational identification of such motifs is made easier\nby the fact that they often appear several times in the upstream region of the\nregulated genes, so that the number of occurrences of relevant motifs is often\nsignificantly larger than expected by pure chance. RESULTS: To exploit this\nfact, we construct sets of genes characterized by the statistical\noverrepresentation of a certain motif in their upstream regions. Then we study\nthe functional characterization of these sets by analyzing their annotation to\nGene Ontology terms. For the sets showing a statistically significant specific\nfunctional characterization, we conjecture that the upstream motif\ncharacterizing the set is a binding site for a transcription factor involved in\nthe regulation of the genes in the set. CONCLUSIONS: The method we propose is\nable to identify many known binding sites in S. cerevisiae and new candidate\ntargets of regulation by known transcription factors. Its application to less\nwell studied organisms is likely to be valuable in the exploration of their\nregulatory interaction network.",
"arxiv_id": "q-bio/0310040",
"authors": [
"Davide Cora\u0027",
"Ferdinando Di Cunto",
"Paolo Provero",
"Lorenzo Silengo",
"Michele Caselle"
],
"categories": [
"q-bio.GN"
],
"journal_ref": "BMC Bioinformatics. 2004 May 11;5(1):57",
"title": "Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrepresented upstream motifs",
"url": "https://arxiv.org/abs/q-bio/0310040"
},
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