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A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics
Joint Authors
Kang, Liying
Li, Shan
Zhao, Xing-Ming
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-06
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced.
It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines.
Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency.
Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs) are widely used in various fields due to the efficiency and robustness of EAs.
In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics.
In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks.
American Psychological Association (APA)
Li, Shan& Kang, Liying& Zhao, Xing-Ming. 2014. A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics. BioMed Research International،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-466013
Modern Language Association (MLA)
Li, Shan…[et al.]. A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics. BioMed Research International No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-466013
American Medical Association (AMA)
Li, Shan& Kang, Liying& Zhao, Xing-Ming. A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-466013
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-466013