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Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics
Joint Authors
Belhaouari, Samir Brahim
Iqbal, Muhammad Javed
Faye, Ibrahima
Md Said, Abas
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-19
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Bioinformatics has been an emerging area of research for the last three decades.
The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding.
The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods.
To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past.
The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins.
The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods.
In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector.
The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth.
American Psychological Association (APA)
Iqbal, Muhammad Javed& Faye, Ibrahima& Belhaouari, Samir Brahim& Md Said, Abas. 2014. Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1048590
Modern Language Association (MLA)
Iqbal, Muhammad Javed…[et al.]. Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics. The Scientific World Journal No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1048590
American Medical Association (AMA)
Iqbal, Muhammad Javed& Faye, Ibrahima& Belhaouari, Samir Brahim& Md Said, Abas. Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1048590
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048590