Predictability of rules in HIV-1 protease cleavage site analysis

Hyeoncheol Kim, Tae Sun Yoon, Yiying Zhang, Anupam Dikshit, Su Shing Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationComputational Science - ICCS 2006
Subtitle of host publication6th International Conference, Proceedings
PublisherSpringer Verlag
Pages830-837
Number of pages8
ISBN (Print)3540343814, 9783540343813
DOIs
Publication statusPublished - 2006
EventICCS 2006: 6th International Conference on Computational Science - Reading, United Kingdom
Duration: 2006 May 282006 May 31

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3992 LNCS - II
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherICCS 2006: 6th International Conference on Computational Science
CountryUnited Kingdom
CityReading
Period06/5/2806/5/31

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kim, H., Yoon, T. S., Zhang, Y., Dikshit, A., & Chen, S. S. (2006). Predictability of rules in HIV-1 protease cleavage site analysis. In Computational Science - ICCS 2006: 6th International Conference, Proceedings (pp. 830-837). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3992 LNCS - II). Springer Verlag. https://doi.org/10.1007/11758525_111