A Class of Pareto Archived Evolution Strategy Algorithms Using Immune Inspired Operators for Ab-Initio Protein Structure Prediction View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2005

AUTHORS

Vincenzo Cutello , Giuseppe Narzisi , Giuseppe Nicosia

ABSTRACT

In this work we investigate the applicability of a multiobjective formulation of the Ab-Initio Protein Structure Prediction (PSP) to medium size protein sequences (46-70 residues). In particular, we introduce a modified version of Pareto Archived Evolution Strategy (PAES) which makes use of immune inspired computing principles and which we will denote by “I-PAES”. Experimental results on the test bed of five proteins from PDB show that PAES, (1+1)-PAES and its modified version I-PAES, are optimal multiobjective optimization algorithms and the introduced mutation operators, mut1 and mut2, are effective for the PSP problem. The proposed I-PAES is comparable with other evolutionary algorithms proposed in literature, both in terms of best solution found and computational cost. More... »

PAGES

54-63

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-32003-6_6

DOI

http://dx.doi.org/10.1007/978-3-540-32003-6_6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1025036044


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