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  1. Pubblicazioni

CMF: a Combinatorial Tool to Find Composite Motifs

Contributo in Atti di convegno
Data di Pubblicazione:
2013
Citazione:
CMF: a Combinatorial Tool to Find Composite Motifs / Leoncini, Mauro; Montangero, Manuela; M., Pellegrini; Panucia Tillan, Karina. - STAMPA. - 7997:(2013), pp. 196-208. ( 7th International Conference on Learning and Intelligent Optimization, LION 7 Catania, ita 7-11 Gennaio 2013) [10.1007/978-3-642-44973-4_21].
Abstract:
Controlling the differential expression of many thousands genes at any given time is a fundamental task of metazoan organisms and this complex orchestration is controlled by the so-called regulatory genome encoding complex regulatory networks. Cis-Regulatory Modules are fundamental units of such networks. To detect Cis-Regulatory Modules “in-silico” a key step is the discovery of recurrent clusters of DNA binding sites for sets of cooperating Transcription Factors. Composite motif is the term often adopted to refer to these clusters of sites. In this paper we describe CMF, a new efficient combinatorial method for the problem of detecting composite motifs, given in input a description of the binding affinities for a set of transcription factors. Testing with known benchmark data, we attain statistically significant better performance against nine state-of-the-art competing methods.
Tipologia CRIS:
Relazione in Atti di Convegno
Keywords:
DNA composite motif, algorithms, computational molecular biology
Elenco autori:
Leoncini, Mauro; Montangero, Manuela; M., Pellegrini; Panucia Tillan, Karina
Autori di Ateneo:
LEONCINI Mauro
MONTANGERO Manuela
Link alla scheda completa:
https://iris.unimore.it/handle/11380/916689
Titolo del libro:
Learning and Intelligent Optimization
Pubblicato in:
LECTURE NOTES IN COMPUTER SCIENCE
Journal
LECTURE NOTES IN COMPUTER SCIENCE
Series
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