Signal finding (pattern discovery) in biological sequences is a fundamental problem in both computer science and molecular biology. From a biological point of view, the knowledge of which motifs are the most frequent in a given set of sequences is only partially informative. In general, one can identify different subsets of sequences, each characterized by different motifs. To superimpose a single set of frequent motifs over the whole dataset is often an oversimplification that do not expose important pieces of information. We propose a de novo framework allowing one to simultaneously build partitions of protein sequences and groups of associated patterns. In this way we are able to individuate a richer set of motifs, each one possibly characterizing only some of the sequences in the whole dataset.

A new protein motif extraction framework based on constrained co-clustering

CORDERO, Francesca;VISCONTI, ALESSIA;BOTTA, Marco
2009

Abstract

Signal finding (pattern discovery) in biological sequences is a fundamental problem in both computer science and molecular biology. From a biological point of view, the knowledge of which motifs are the most frequent in a given set of sequences is only partially informative. In general, one can identify different subsets of sequences, each characterized by different motifs. To superimpose a single set of frequent motifs over the whole dataset is often an oversimplification that do not expose important pieces of information. We propose a de novo framework allowing one to simultaneously build partitions of protein sequences and groups of associated patterns. In this way we are able to individuate a richer set of motifs, each one possibly characterizing only some of the sequences in the whole dataset.
24th Annual ACM Symposium on Applied Computing
Honolulu, Hawaii
March 8-12 2009
Proceedings of the 24th Annual ACM Symposium on Applied Computing
ACM Press
776
781
Cordero F.; Visconti A.; Botta M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/71909
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