Predictability of rules in HIV-1 protease cleavage site analysis

Authors:
Hyeoncheol Kim;Tae-Sun Yoon;Yiying Zhang;Anupam Dikshit;Su-Shing Chen
Affiliations:
Dept. of Computer Science Education, Korea University, Seoul, Korea;Dept. of Computer Science Education, Korea University, Seoul, Korea;Computer & Info. Sciences and Engineering, University of Florida, Gainesville, FL;Computer & Info. Sciences and Engineering, University of Florida, Gainesville, FL;Computer & Info. Sciences and Engineering, University of Florida, Gainesville, FL
Venue:
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part II
Year:
2006

Citing 6
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Abstract

Symbolic rules play an important role in HIV-1 protease cleavage site prediction. Recently, some studies have done on extraction of the prediction rules with some success. In this paper, we demonstrated a decompositional approach for rule extraction from nonlinear neural networks. We also compared the prediction rules to the ones extracted by other approaches and methods. Empirical experiments are also shown.