Post Docking Filtering Using Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InCollection{garmendia-doval:2004:GPTP,

• author = "A. Beatriz Garmendia-Doval and Julian Miller and S. David Morley",
• title = "Post Docking Filtering Using Cartesian Genetic Programming",
• booktitle = "Genetic Programming Theory and Practice {II}",
• year = "2004",
• editor = "Una-May O'Reilly and Tina Yu and Rick L. Riolo and Bill Worzel",
• chapter = "14",
• pages = "225--244",
• address = "Ann Arbor",
• month = "13-15 " # may,
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, cartesian genetic programming, molecular docking prediction, virtual screening, machine learning, evolutionary algorithms, neutral evolution",
• ISBN = "0-387-23253-2",
• DOI = "doi:10.1007/0-387-23254-0_14",
• abstract = "Structure-based virtual screening is a technology increasingly used in drug discovery. Although successful at estimating binding modes for input ligands, these technologies are less successful at ranking true hits correctly by binding free energy. This chapter presents the automated removal of false positives from virtual hit sets, by evolving a post docking filter using Cartesian Genetic Programming(CGP). We also investigate characteristics of CGP for this problem and confirm the absence of bloat and the usefulness of neutral drift.",
• notes = "part of \cite{oreilly:2004:GPTP2}",

}

Genetic Programming entries for A Beatriz Garmendia-Doval Julian F Miller S David Morley

Citations