By Topic

Parallel genetic algorithms on PARAM for conformation of biopolymers

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Sundararajan, V. ; Applications Group, Centre for Dev. of Adv. Comput., Pune, India ; Kolaskar, A.S.

A software is developed using genetic algorithms to predict the structure of a polypeptide chain. The algorithm is based on the principle of evolution and it improves the solution of the posed problem by genetic operations crossovers and mutations. Dihedral angles (φ,ψ) are taken as the basic variables for the structure of the molecules and genetic operations are carried over on a population of binary strings of (φ,ψ) angles. First, a sequential code is developed in FORTRAN on a standard workstation. A parallel version of the program is implemented on a distributed computing platform PARAM, developed by CDAC. The methodology and the practical aspects of the algorithm is presented with case studies of a dipeptide and an octapeptide. The usefulness of the migration model, developed for the first time, in achieving efficiency is stressed. The migration model proved to be more efficient and the minimisation for the octapeptide improved from 2% to 10%. This improvement is expected to be more pronounced for larger molecules

Published in:

High Performance Computing, 1996. Proceedings. 3rd International Conference on

Date of Conference:

19-22 Dec 1996