Hybrid particle swarm optimization technique for protein structure prediction using 2D off-lattice model

2Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Protein Structure Prediction with lowest energy from its primary sequence of amino acids is a complex and challenging problem in computational biology, addressed by researchers using heuristic optimization techniques. Particle Swarm Optimization (PSO), a heuristic optimization technique having strong global search capability but often stuck at local optima while solving complex optimization problem. To prevent local optima problem, PSO with local search (HPSOLS) capability has been proposed in the paper to predict structure of protein using 2D off-lattice model. HPSOLS is applied on artificial and real protein sequences to conform the performance and robustness for solving protein structure prediction having lowest energy. Results are compared with other algorithms demonstrating efficiency of the proposed model. © 2013 Springer International Publishing.

Cite

CITATION STYLE

APA

Jana, N. D., & Sil, J. (2013). Hybrid particle swarm optimization technique for protein structure prediction using 2D off-lattice model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8298 LNCS, pp. 193–204). https://doi.org/10.1007/978-3-319-03756-1_17

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free