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Sequence information gain based motif analysis

Author
Maynou, J.; Pairó, E.; Marco, S.; Perera, A.
Type of activity
Journal article
Journal
BMC bioinformatics
Date of publication
2015-11-09
Volume
16
Number
377
First page
1
Last page
13
DOI
https://doi.org/10.1186/s12859-015-0811-x Open in new window
Project funding
Serious Games on Heart Failure patients. Estimation of their benefits on the Spanish Health System
Repository
http://hdl.handle.net/2117/99688 Open in new window
URL
http://www.biomedcentral.com Open in new window
Abstract
Background: The detection of regulatory regions in candidate sequences is essential for the understanding of the regulation of a particular gene and the mechanisms involved. This paper proposes a novel methodology based on information theoretic metrics for finding regulatory sequences in promoter regions. Results: This methodology (SIGMA) has been tested on genomic sequence data for Homo sapiens and Mus musculus. SIGMA has been compared with different publicly available alternatives for motif de...
Citation
Maynou, J., Pairó, E., Marco, S., Perera, A. Sequence information gain based motif analysis. "BMC bioinformatics", 9 Novembre 2015, vol. 16, núm. 377, p. 1-13.
Group of research
B2SLab - Bioinformatics and Biomedical Signals Laboratory
CREB - Biomedical Engineering Research Centre

Participants

  • Maynou Fernández, Joan  (author)
  • Pairó, Erola  (author)
  • Marco, Santiago  (author)
  • Perera Lluna, Alexandre  (author)

Attachments