Optimizing big data in bioinformatics with swarm algorithms

Optimizing big data in bioinformatics with swarm algorithms

This paper describes the application of swarm algorithms on bioinformatics data namely protein sequences. The big data that exists in bioinformatics domains require an intelligent method that capable to increase the performance of classification as well as discovering the knowledge. The work optimiz...

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Published in:Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013
Main Author: Abdul-Rahman S.; Bakar A.A.; Mohamed-Hussein Z.-A.
Format: Conference paper
Language:English
Published: 2013
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84900374709&doi=10.1109%2fCSE.2013.158&partnerID=40&md5=53a1a5377066bc6104cff590aec636ec
id 2-s2.0-84900374709
spelling 2-s2.0-84900374709
Abdul-Rahman S.; Bakar A.A.; Mohamed-Hussein Z.-A.
Optimizing big data in bioinformatics with swarm algorithms
2013
Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013


10.1109/CSE.2013.158
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84900374709&doi=10.1109%2fCSE.2013.158&partnerID=40&md5=53a1a5377066bc6104cff590aec636ec
This paper describes the application of swarm algorithms on bioinformatics data namely protein sequences. The big data that exists in bioinformatics domains require an intelligent method that capable to increase the performance of classification as well as discovering the knowledge. The work optimizes the big features that exist in protein sequences using the two-tier hybrid model by applying the filter and wrapper method. The use of swarm algorithm namely particle swarm optimization has improved the classification accuracy as the features are optimized prior to classification. The study also compares the performance of swarm algorithms with the standard searching method. © 2013 IEEE.


English
Conference paper
author Abdul-Rahman S.; Bakar A.A.; Mohamed-Hussein Z.-A.
spellingShingle Abdul-Rahman S.; Bakar A.A.; Mohamed-Hussein Z.-A.
Optimizing big data in bioinformatics with swarm algorithms
author_facet Abdul-Rahman S.; Bakar A.A.; Mohamed-Hussein Z.-A.
author_sort Abdul-Rahman S.; Bakar A.A.; Mohamed-Hussein Z.-A.
title Optimizing big data in bioinformatics with swarm algorithms
title_short Optimizing big data in bioinformatics with swarm algorithms
title_full Optimizing big data in bioinformatics with swarm algorithms
title_fullStr Optimizing big data in bioinformatics with swarm algorithms
title_full_unstemmed Optimizing big data in bioinformatics with swarm algorithms
title_sort Optimizing big data in bioinformatics with swarm algorithms
publishDate 2013
container_title Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013
container_volume
container_issue
doi_str_mv 10.1109/CSE.2013.158
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84900374709&doi=10.1109%2fCSE.2013.158&partnerID=40&md5=53a1a5377066bc6104cff590aec636ec
description This paper describes the application of swarm algorithms on bioinformatics data namely protein sequences. The big data that exists in bioinformatics domains require an intelligent method that capable to increase the performance of classification as well as discovering the knowledge. The work optimizes the big features that exist in protein sequences using the two-tier hybrid model by applying the filter and wrapper method. The use of swarm algorithm namely particle swarm optimization has improved the classification accuracy as the features are optimized prior to classification. The study also compares the performance of swarm algorithms with the standard searching method. © 2013 IEEE.
publisher
issn
language English
format Conference paper
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record_format scopus
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