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 transcritpion factors. Its application to less well studied organisms is likely to be valuable in the exploration of their regulatory interaction network.
| Original language | English |
|---|---|
| Article number | 57 |
| Journal | BMC Bioinformatics |
| Volume | 5 |
| DOIs | |
| Publication status | Published - May 11 2004 |
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ASJC Scopus subject areas
- Medicine(all)
- Structural Biology
- Applied Mathematics
Cite this
Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrepresented upstream motifs. / Corà, Davide; Di Cunto, Ferdinando; Provero, Paolo; Silengo, Lorenzo; Caselle, Michele.
In: BMC Bioinformatics, Vol. 5, 57, 11.05.2004.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrepresented upstream motifs
AU - Corà, Davide
AU - Di Cunto, Ferdinando
AU - Provero, Paolo
AU - Silengo, Lorenzo
AU - Caselle, Michele
PY - 2004/5/11
Y1 - 2004/5/11
N2 - 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 transcritpion factors. Its application to less well studied organisms is likely to be valuable in the exploration of their regulatory interaction network.
AB - 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 transcritpion 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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U2 - 10.1186/1471-2105-5-57
DO - 10.1186/1471-2105-5-57
M3 - Article
C2 - 15137914
AN - SCOPUS:2942580909
VL - 5
JO - BMC Bioinformatics
JF - BMC Bioinformatics
SN - 1471-2105
M1 - 57
ER -