Metaheuristics based de novo protein sequencing: A new approach

Authors:
Jean-Charles Boisson;Laetitia Jourdan;El-Ghazali Talbi
Affiliations:
INRIA Lille Nord Europe, Parc scientifique de la Haute-Borne Bítiment A, Park Plaza, Bureau 208 40, Avenue Halley, 59650 Villeneuve d'Ascq Cedex, France;INRIA Lille Nord Europe, Parc scientifique de la Haute-Borne Bítiment A, Park Plaza, Bureau 208 40, Avenue Halley, 59650 Villeneuve d'Ascq Cedex, France;INRIA Lille Nord Europe, Parc scientifique de la Haute-Borne Bítiment A, Park Plaza, Bureau 208 40, Avenue Halley, 59650 Villeneuve d'Ascq Cedex, France
Venue:
Applied Soft Computing
Year:
2011

Citing 6
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Abstract

In this article, a new approach is proposed for the de novo protein sequencing problem. The aim is to find the sequence of an experimental protein from only experimental data, i.e. without databases. To do so, a three-step model called SSO for Shape, Sequence and Order has been designed. No prior knowledge in genomics nor protein databases are used. Here we modelized de novo protein sequencing as a combinatorial optimisation problem and propose cooperative metaheuristics to solve it. Results are assessed on experimental proteins and proved the feasibility of this approach.