Referenced Items are not available for this document.
This paper presents a novel approach, namely SSVS, to improve the secondary structure prediction of proteins. In this work, a Radial Basis Function Neural Network is trained to combine different answers found by different secondary structure prediction techniques to produce superior answers. 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), 2010 IEEE/ACS International Conference on
Date of Conference: 16-19 May 2010
- Page(s):
- 1 - 7
- Print ISBN:
- 978-1-4244-7716-6
- INSPEC Accession Number:
- 11558577
- Conference Location :
- Hammamet
- Digital Object Identifier :
- 10.1109/AICCSA.2010.5586931
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