Predicting 3D structure of proteins from genomic sequences: A genetic algorithm approach

Author

Dongardive, Jyotshna ; Abraham, S.

Author_Institution

Dept. of Comput. Sci., Univ. of Mumbai, Mumbai, India

fYear

2013

Firstpage

1207

Lastpage

1212

Abstract

The paper proposes a methodology for predicting 3D structure of proteins using genetic algorithm. It uses genomic sequences for the experimental purpose. In order to give a complete representation of known and unknown genomic sequences of similar kind, the known collection of sequences are made to evolve. The evolved sequences are subjected to offer consensus of the sequences. This consensus is used for generating a primary protein sequence, which is used for predicting the 3D structure of protein. The genomic sequences used for the study are that of Human Pappillamovirus, which causes cervical cancer, among many other diseases.

Keywords

bioinformatics; cancer; genetic algorithms; genomics; microorganisms; proteins; 3D protein structure prediction; cervical cancer; diseases; genetic algorithm approach; genomic sequence consensus; human pappillamovirus; known genomic sequence representation; primary protein sequence generation; unknown genomic sequence representation; Bioinformatics; Computational modeling; Genetic algorithms; Genomics; Hidden Markov models; Proteins; Three-dimensional displays; Consensus; Genetic Algorithm; Genomic Sequences; Protein Structure Prediction; Weight Matrix Algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on

Conference_Location

Mysore

Print_ISBN

978-1-4799-2432-5

Type

conf

DOI

10.1109/ICACCI.2013.6637349

Filename

6637349