Mining HIV protease cleavage data using genetic programming with a sum-product function

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{ZhengRongYang:2004:B,
  author =       "Zheng Rong Yang and Andrew R. Dalby and Jing Qiu",
  title =        "Mining {HIV} protease cleavage data using genetic
                 programming with a sum-product function",
  journal =      "Bioinformatics",
  year =         "2004",
  volume =       "20",
  number =       "18",
  pages =        "3398--3405",
  keywords =     "genetic algorithms, genetic programming, HIV protease,
                 enzyme, min-max scoring function, sum-production
                 scoring function",
  ISSN =         "1367--4803",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:10.1.1.612.3378",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.612.3378",
  URL =          "http://bioinformatics.oxfordjournals.org/content/early/2004/07/15/bioinformatics.bth414.full.pdf",
  DOI =          "doi:10.1093/bioinformatics/bth414",
  abstract =     "Motivation: In order to design effective HIV
                 inhibitors, studying and understanding the mechanism of
                 HIV protease cleavage specification is critical.
                 Various methods have been developed to explore the
                 specificity of HIV protease cleavage activity. However,
                 success in both extracting discriminant rules and
                 maintaining high prediction accuracy is still
                 challenging. The earlier study had employed genetic
                 programming with a min-max scoring function to extract
                 discriminant rules with success. However, the decision
                 will finally be degenerated to one residue making
                 further improvement of the prediction accuracy
                 difficult. The challenge of revising the min-max
                 scoring function so as to improve the prediction
                 accuracy motivated this study.

                 Results: This paper has designed a new scoring function
                 called a sum-product function for extracting HIV
                 protease cleavage discriminant rules using genetic
                 programming methods. The experiments show that the new
                 scoring function is superior to the min-max scoring
                 function. Availability: The software package can be
                 obtained by request to Dr Zheng Rong Yang.

                 Contact: z.r.yang@ex.ac.uk",
  notes =        "http://bioinformatics.oxfordjournals.org/cgi/content/abstract/20/18/3398
                 1 Department of Computer Science and 2 Department of
                 Biology Sciences, Exeter University, UK PMID: 15256407
                 [PubMed - indexed for MEDLINE]",
}

Genetic Programming entries for Zheng Rong Yang Andrew Rowland Dalby Jing Qiu

Citations