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Please use this identifier to cite or link to this item: http://hdl.handle.net/10481/33440

Title: CisMiner: Genome-Wide In-Silico Cis-Regulatory Module Prediction by Fuzzy Itemset Mining
Authors: Navarro Luzón, Carmen
López Domingo, Francisco Javier
Cano Gutiérrez, Carlos
García Alcalde, Fernando
Blanco Morón, Armando
Issue Date: 2014
Abstract: Eukaryotic gene control regions are known to be spread throughout non-coding DNA sequences which may appear distant from the gene promoter. Transcription factors are proteins that coordinately bind to these regions at transcription factor binding sites to regulate gene expression. Several tools allow to detect significant co-occurrences of closely located binding sites (cis-regulatory modules, CRMs). However, these tools present at least one of the following limitations: 1) scope limited to promoter or conserved regions of the genome; 2) do not allow to identify combinations involving more than two motifs; 3) require prior information about target motifs. In this work we present CisMiner, a novel methodology to detect putative CRMs by means of a fuzzy itemset mining approach able to operate at genome-wide scale. CisMiner allows to perform a blind search of CRMs without any prior information about target CRMs nor limitation in the number of motifs. CisMiner tackles the combinatorial complexity of genome-wide cis-regulatory module extraction using a natural representation of motif combinations as itemsets and applying the Top-Down Fuzzy Frequent- Pattern Tree algorithm to identify significant itemsets. Fuzzy technology allows CisMiner to better handle the imprecision and noise inherent to regulatory processes. Results obtained for a set of well-known binding sites in the S. cerevisiae genome show that our method yields highly reliable predictions. Furthermore, CisMiner was also applied to putative in-silico predicted transcription factor binding sites to identify significant combinations in S. cerevisiae and D. melanogaster, proving that our approach can be further applied genome-wide to more complex genomes. CisMiner is freely accesible at: http://genome2.ugr.es/cisminer. CisMiner can be queried for the results presented in this work and can also perform a customized cis-regulatory module prediction on a query set of transcription factor binding sites provided by the user.
Sponsorship: This work has been carried out as part of projects PI-0710-2013 of J. A., Sevilla and TIN2013-41990-R of DGICT, Madrid.
Publisher: Public Library of Science (PLOS)
Keywords: Genome analysis
Genome complexity
Genome evolution
Genomic databases
Invertebrate genomics
Saccharomyces cerevisiae
Sequence motif analysis
Transcription factors
URI: http://hdl.handle.net/10481/33440
ISSN: 1932-6203
Rights : Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License
Citation: Navarro, C.; et al. CisMiner: Genome-Wide In-Silico Cis-Regulatory Module Prediction by Fuzzy Itemset Mining. Plos One, 9(9): e108065 (2014). [http://hdl.handle.net/10481/33440]
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