alexa A Swarm Intelligence Heuristic Approach to Longest Comm
ISSN: 2153-0769

Metabolomics:Open Access
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A Swarm Intelligence Heuristic Approach to Longest Common Subsequence Problem for Arbitrary Number of Sequences

Ali Teoman Unay1 and Meral Guzey2*

1Department of Intelligent Computing Systems, Izmir University of Economics, Izmir, Turkey

2Department of Math and Life Sciences, Main campus of University Maryland University College (UMUC), USA

*Corresponding Author:
Meral Guzey
Department of Math and Life Sciences
Main campus of University Maryland University College (UMUC), USA
E-mail: [email protected]

Received date: June 25, 2013; Accepted date: August 06, 2013; Published date: August 13, 2013

Citation: Unay AT, Guzey M (2013) A Swarm Intelligence Heuristic Approach to Longest Common Subsequence Problem for Arbitrary Number of Sequences. Metabolomics 3:120. doi: 10.4172/2153-0769.1000120

Copyright: © 2013 Unay AT, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

Abstract

Personalized cancer care strategies involving sequencing requires accuracy. We aimed to develop a novel
approach to solve the longest common subsequence problem, which is a common computer science problem in the field of bioinformatics to facilitate the next generation sequencing of cancer biomarkers. We are using particle swarm optimization heuristic technique, which uses a novel “Occurrence Listing” (OL) technique as the evaluation function. This aims to keep lists of the sequence elements and offers criteria to evaluate randomly generated population of sequences.

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