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Identification of promoter regions in genomic sequences by 1-dimensional constraint clustering
A. Bertoni, M. Rè, F. Saccà, G. Valentini
162 - 169
10.3233/978-1-60750-972-1-162
Frontiers in Artificial Intelligence and Applications
Volume 234: Neural Nets WIRN11
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.

$35.00 / €27.50 / £22.00
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