PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Identification of promoter regions in genomic sequences by 1-dimensional constraint clustering
Alberto Bertoni, Matteo Re, Francesco Sacca and Giorgio Valentini
In: Frontiers in Artificial Intelligence and Applications (2011) IOS Press , pp. 162-169. ISBN 978-1-60750-971-4

Abstract

Size constrained clustering has been recently proposed to embed “a priori” knowledge in clustering methods. By exploiting the “string property” we propose an exact and efficient algorithm based on dynamic programming techniques to solve size-constrained one-dimensional clustering problems. We show the applicability of the proposed method in a difficult computational biology problem: the prediction of the transcription start sites of genes. The obtained experimental results clearly show the potential of the proposed approach when compared with previously published methods.

EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:9161
Deposited By:Giorgio Valentini
Deposited On:21 February 2012