A fuzzy based approach for prediction of biological activities of HIV -1 protease inhibitor compounds

Author

Parthiban, Latha ; Parthiban, Rangasamy

Author_Institution

Dept. of Comput. Sci. & Eng., SSN Coll. of Eng., Chennai, India

fYear

2011

fDate

7-9 Sept. 2011

Firstpage

57

Lastpage

61

Abstract

A neuro-fuzzy based approach for predicting the HIV-1 inhibitor compounds activity has been designed when the molecular descriptor attributes of the compound are known. Standard Fuzzy ARTMAP (FAM) is provided with 196 data sets which is divided into 176 training data and 20 test data. The normalized data is given to the FAM network and the result indicates whether the compound is a suitable inhibitor or not. The result analysis is done with/ without GA for the dataset and GA-FAMR algorithm is used to optimize the relevance´s assigned to the training data and the accuracy obtained is 93.09%.

Keywords

biology computing; data handling; fuzzy neural nets; genetic algorithms; molecular biophysics; GA-FAMR algorithm; HIV-1 protease inhibitor compound; biological activity prediction; fuzzy ARTMAP; genetic algorithm; molecular descriptor attribute; neuro-fuzzy based approach; Biology; Compounds; Genetic algorithms; Inhibitors; Neural networks; Optimization; Training; Fuzzy ARTMAP; Genetic algorithm; HIV-1; Prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Agent and Multi-Agent Systems (IAMA), 2011 2nd International Conference on

Conference_Location

Chennai

Print_ISBN

978-1-4577-0876-3

Type

conf

DOI

10.1109/IAMA.2011.6049004

Filename

6049004