DocumentCode
2960245
Title
Fuzz-SSVS: A Fuzzy logic based voting scheme to improve protein secondary structure prediction
Author
Taheri, Javid ; Zomaya, Albert Y. ; Delicato, Flávia C. ; Pires, Paulo F.
Author_Institution
Centre for Distrib. & High Performance Comput., Univ. of Sydney, Sydney, NSW, Australia
fYear
2011
fDate
27-30 Dec. 2011
Firstpage
60
Lastpage
66
Abstract
This paper presents a novel approach, Fuzz-SSVS, to improve the secondary structure prediction of proteins. In this work, a Sugeno based Fuzzy System is trained to act as a voting system to combine results of several secondary structure prediction techniques and produce superior answers. Fuzz-SSVS is tested with three of the well-known benchmarks in this field. The results demonstrate the superiority of the proposed technique even in the case of formidable sequences.
Keywords
bioinformatics; data analysis; fuzzy logic; fuzzy set theory; proteins; Fuzz-SSVS; Sugeno based fuzzy system; formidable sequences; fuzzy logic based voting scheme; protein secondary structure prediction; voting system; Accuracy; Amino acids; Benchmark testing; Fuzzy systems; Prediction methods; Proteins; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Systems and Applications (AICCSA), 2011 9th IEEE/ACS International Conference on
Conference_Location
Sharm El-Sheikh
ISSN
2161-5322
Print_ISBN
978-1-4577-0475-8
Electronic_ISBN
2161-5322
Type
conf
DOI
10.1109/AICCSA.2011.6126592
Filename
6126592
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