DocumentCode
1992722
Title
Protein Secondary Structure Prediction Using Genetic Neural Support Vector Machines
Author
Reyaz-Ahmed, Anjum ; Zhang, Yan-Qing
Author_Institution
Georgia State Univ., Atlanta
fYear
2007
fDate
14-17 Oct. 2007
Firstpage
1355
Lastpage
1359
Abstract
Support vector machines (SVM) have shown strong generalization ability in a number of application areas, including protein structure prediction. In this paper a new tertiary classifier is introduced that makes use of support vector machines as neurons in a neural network architecture. This network is optimized using genetic algorithms. The novel tertiary classifier is better than most available techniques.
Keywords
genetic algorithms; molecular biophysics; neural nets; proteins; support vector machines; genetic algorithms; genetic neural support vector machines; neurons; optimization; protein secondary structure prediction; Biological neural networks; Computer architecture; Encoding; Genetic algorithms; Machine learning; Neural networks; Neurons; Proteins; Support vector machine classification; Support vector machines; proteins; structure prediction; support vector machines; tertiary classifier;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Bioengineering, 2007. BIBE 2007. Proceedings of the 7th IEEE International Conference on
Conference_Location
Boston, MA
Print_ISBN
978-1-4244-1509-0
Type
conf
DOI
10.1109/BIBE.2007.4375746
Filename
4375746
Link To Document