|
DSpace@nitr >
National Institue of Technology- Rourkela >
Conference Papers >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/1105
|
| Title: | Improved Protein Structural Class Prediction Using Genetic Algorithm and Artificial Immune System |
| Authors: | Sahu, S S
Panda, G
Nanda, S Jagannath |
| Issue Date: | 2009 |
| Publisher: | PSG College of Technology |
| Citation: | World Congress on Nature and Biologically Inspired Computiing -NaBIC 2009, 9-11 Dec 2009, Coimbatore,India |
| Abstract: | Predicting the structure of a protein from primary sequence
is one of the challenging problems in Molecular
biology. In this context, protein structural class information
provides a key idea of their structure and also other features
related to the biological function. In this paper we present a
new optimization approach based on Genetic algorithm (GA)
and artificial immune system (AIS) for predicting the protein
structural class. It uses the maximum component coefficient
principle in association with the amino acid composition
feature vector to efficiently classify the protein structures.
The effectiveness is evaluated by comparing the results with
that obtained from other existing methods using a standard
database. Especially for all and + class protein, the
rate of accurate prediction by the proposed methods is much
higher than their counterparts. |
| Description: | Copyright for the paper belongs to proceedings publisher |
| URI: | http://hdl.handle.net/2080/1105 |
| Appears in Collections: | Conference Papers
|
Files in This Item:
| File |
Description |
Size | Format |
|---|
| NaBIC2009.pdf | | 242Kb | Adobe PDF | View/Open |
|
Show full item record
All items in DSpace are protected by copyright, with all rights reserved.
|
