Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5589991 | Gene Reports | 2017 | 16 Pages |
Abstract
Finding the native structure of a protein initially from its amino acid sequence remains one of the most challenging open problems in Bioinformatics and molecular biology. Protein structure prediction plays a critical part in protein construction and mapping analysis, drug design and any other biological applications. Extracting good representation from protein sequence is fundamental to this prediction task. The multi-objective optimization tends to be more effective than other techniques in complex problems. The protein structure prediction problem is solved using Diversity Controlled Self-Adaptive cuckoo algorithm. MODCSA-CA, an improved version of Self-Adaptive Differential Evolution (SaDE), to check the diversity of individuals and local search to sustain a balance between exploration and exploitation. This subject looks into the application of cuckoo search (CS) algorithm on the protein structure prediction problem. Results point MODCSA-CA as a competitive approach for total energy and conformation similarity metrics. Comparability of the statistical results demonstrates that CS outperforms other algorithms in a meaningful manner.
Keywords
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Biochemistry, Genetics and Molecular Biology
Genetics
Authors
D. Ramyachitra, A. Ajeeth,