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.

CMF: a Combinatorial Tool to Find Composite Motifs / Leoncini, Mauro; Montangero, Manuela; M., Pellegrini; PANUCIA TILLAN, Karina. - STAMPA. - 7997:(2013), pp. 196-208. ((Intervento presentato al convegno 7th International Conference on Learning and Intelligent Optimization, LION 7 tenutosi a Catania, ita nel 7-11 Gennaio 2013 [10.1007/978-3-642-44973-4_21].

CMF: a Combinatorial Tool to Find Composite Motifs

LEONCINI, Mauro;MONTANGERO, Manuela;PANUCIA TILLAN, Karina
2013

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.
7th International Conference on Learning and Intelligent Optimization, LION 7
Catania, ita
7-11 Gennaio 2013
7997
196
208
Leoncini, Mauro; Montangero, Manuela; M., Pellegrini; PANUCIA TILLAN, Karina
CMF: a Combinatorial Tool to Find Composite Motifs / Leoncini, Mauro; Montangero, Manuela; M., Pellegrini; PANUCIA TILLAN, Karina. - STAMPA. - 7997:(2013), pp. 196-208. ((Intervento presentato al convegno 7th International Conference on Learning and Intelligent Optimization, LION 7 tenutosi a Catania, ita nel 7-11 Gennaio 2013 [10.1007/978-3-642-44973-4_21].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/916689
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