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Investigating stochastic diffusion search in DNA sequence assembly problem

Investigating stochastic diffusion search in DNA sequence assembly problem

Al-Rifaie, Fatimah Majid and Al-Rifaie, Mohammad Majid ORCID: 0000-0002-1798-9615 (2015) Investigating stochastic diffusion search in DNA sequence assembly problem. In: Proceedings of 2015 SAI Intelligent Systems Conference (IntelliSys). 10-11 November 2015 London, UK. IEEExplore . Institute of Electrical and Electronics Engineers (IEEE), New Jersey, USA, pp. 625-631. ISBN 978-1467376068 (doi:https://doi.org/10.1109/IntelliSys.2015.7361205)

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Abstract

This paper introduces a novel study on the performance of Stochastic Diffusion Search (SDS) - swarm intelligence algorithm - to address DNA sequence assembly problem. This is an NP-hard problem and one of the primary problems in computational molecular biology that requires optimisation methodologies to reconstruct the original DNA sequence. In this work, SDS algorithm is adapted for the first time for this purpose and several experiments are run in order to evaluate the performance of the presented technique over several frequently used benchmarks. Given the promising results of the newly proposed algorithm and its success in assembling the input fragments, its behaviour is further analysed, thus shedding light on the process through which the algorithm conducts the task. Additionally the performance of the algorithm is compared against several other techniques, demonstrating its weaknesses and strength in the experiments presented in the paper.

Item Type: Conference Proceedings
Title of Proceedings: Proceedings of 2015 SAI Intelligent Systems Conference (IntelliSys). 10-11 November 2015 London, UK
Uncontrolled Keywords: Stochastic diffusion search; DNA sequence assembly
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group: Faculty of Liberal Arts & Sciences > Computational Science & Engineering Group (CSEH)
Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Faculty of Engineering & Science
Related URLs:
Last Modified: 04 Mar 2022 13:07
URI: http://gala.gre.ac.uk/id/eprint/21001

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