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Comparison of parallel multi-objective approaches to protein structure prediction

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Abstract

Protein structure prediction (PSP) is an open problem with many useful applications in disciplines such as medicine, biology and biochemistry. As this problem presents a vast search space and the analysis of each protein structure requires a significant amount of computing time, it is necessary to take advantage of high-performance parallel computing platforms as well as to define efficient search procedures in the space of possible protein conformations. In this paper we compare two parallel procedures for PSP which are based on different multi-objective optimization approaches, i.e. PAES (Knowles and Corne in Proc. Congr. Evol. Comput. 1:98–105, 1999) and NSGA2 (Deb et al. in IEEE Trans. Evol. Comput. 6:182–197, 2002). Although both procedures include techniques to take advantage of known protein structures and strategies to simplify the search space through the so-called rotamer library and adaptive mutation operators, they present different profiles with respect to their implicit parallelism.

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Authors and Affiliations

  1. Department of Computer Architecture and Computer Technology, CITIC-UGR University of Granada, Granada, Spain

    J. C. Calvo, J. Ortega & M. Anguita

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  1. J. C. Calvo
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  2. J. Ortega
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  3. M. Anguita
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Correspondence to J. C. Calvo.

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Calvo, J.C., Ortega, J. & Anguita, M. Comparison of parallel multi-objective approaches to protein structure prediction. J Supercomput 58, 253–260 (2011). https://doi.org/10.1007/s11227-009-0368-4

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  • DOI: https://doi.org/10.1007/s11227-009-0368-4

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