A Heterogeneous Parallel Ecologically-Inspired Approach Applied to the 3D-AB Off-Lattice Protein Structure Prediction Problem

This paper applies a heterogeneous parallel ecology-inspired algorithm (pECO) to solve a complex problem from bioinformatics. The ecological-inspired algorithm represents a new perspective to develop cooperative evolutionary algorithms. Different algorithms are applied to compose the computational ecosystem in a heterogeneous model. The aim is to search low energy conformations for the Protein Structure Prediction problem, concerning the 3D-AB off-lattice model. Being a problem that demands a lot of computational effort, a parallel master-slave architecture is employed in order to allow the application of the computational ecosystem in a reasonable computing time. From the results, the pECO approach obtained the best conformation for the 13 amino-acid long sequence and competitive results for the other sequences.

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