A local search appproach for transmembrane segment and signal peptide discrimination

Authors:
Sami Laroum;Dominique Tessier;Béatrice Duval;Jin-Kao Hao
Affiliations:
UR1268 Biopolymères Interactions Assemblages, INRA, Nantes, France;UR1268 Biopolymères Interactions Assemblages, INRA, Nantes, France;LERIA, 2 Boulevard Lavoisier, Angers, France;LERIA, 2 Boulevard Lavoisier, Angers, France
Venue:
EvoBIO'10 Proceedings of the 8th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Year:
2010

Citing 3
Cited 1

Stochastic Local Search: Foundations & Applications

Stochastic Local Search: Foundations & Applications
Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences

Bioinformatics
SPOCTOPUS

Bioinformatics

Multi-neighborhood search for discrimination of signal peptides and transmembrane segments

EvoBIO'11 Proceedings of the 9th European conference on Evolutionary computation, machine learning and data mining in bioinformatics

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Abstract

Discriminating between secreted and membrane proteins is a challenging task. This is particularly true for discriminating between transmembrane segments and signal peptides because they have common biochemical properties. In this paper, we introduce a new predictive method called LSTranslocon (Local Search Translocon) based on a Local Search methodology. The method takes advantage of the latest knowledge in the field to model the biological behaviors of proteins with the aim of ensuring good prediction. The LS Prediction approach is assessed on a constructed data set from Swiss-Prot database and compared with one of the best methods from the literature.