Publication Date:
2013
Short description:
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.
Iris type:
Relazione in Atti di Convegno
Keywords:
DNA composite motif, algorithms, computational molecular biology
List of contributors:
Leoncini, Mauro; Montangero, Manuela; M., Pellegrini; Panucia Tillan, Karina
Book title:
Learning and Intelligent Optimization
Published in: