Title :
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
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;
Conference_Titel :
Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on
Conference_Location :
Mysore
Print_ISBN :
978-1-4799-2432-5
DOI :
10.1109/ICACCI.2013.6637349
