Referenced Items are not available for this document.
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.
Published in:
Computer Systems and Applications (AICCSA), 2011 9th IEEE/ACS International Conference on
Date of Conference: 27-30 Dec. 2011
- Page(s):
- 60 - 66
- ISSN :
- 2161-5322
- E-ISBN :
- 978-1-4577-0474-1
- Print ISBN:
- 978-1-4577-0475-8
- INSPEC Accession Number:
- 12475405
- Conference Location :
- Sharm El-Sheikh
- Digital Object Identifier :
- 10.1109/AICCSA.2011.6126592
- Product Type:
- Conference Publications
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