Advances in the Application of Machine Learning Techniques in Drug Discovery, Design and Development

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

@InProceedings{barrett:2005:WSC,
  author =       "S. J. Barrett and W. B. Langdon",
  title =        "Advances in the Application of Machine Learning
                 Techniques in Drug Discovery, Design and Development",
  booktitle =    "Applications of Soft Computing: Recent Trends",
  year =         "2006",
  editor =       "Ashutosh Tiwari and Joshua Knowles and 
                 Erel Avineri and Keshav Dahal and Rajkumar Roy",
  series =       "Advances in Soft Computing",
  volume =       "36",
  pages =        "99--110",
  address =      "On the World Wide Web",
  month =        "19 " # sep # " - 7 " # oct # " 2005",
  organisation = "World Federation of Soft Computing (WFSC), European
                 Neural Network Society (ENNS), North American Fuzzy
                 Information Processing Society (NAFIPS), European
                 Society for Fuzzy Logic and Technology (EUSFLAT), and
                 International Fuzzy Systems Association (IFSA)",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming,
                 Pharmaceutical applications, Drug design, Particle
                 swarm optimisation, Support vector machines",
  ISBN =         "3-540-29123-7",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/barrett_2005_WSC.pdf",
  URL =          "http://isxp1010c.sims.cranfield.ac.uk/Papers/paper196.pdf",
  URL =          "https://link.springer.com/chapter/10.1007/978-3-540-36266-1_10",
  size =         "21 pages",
  old_abstract = "Pharmaceutical discovery and development is a cascade
                 of extremely complex and costly research encompassing
                 many facets from: therapeutic target identification and
                 bioinformatics study, candidate drug discovery and
                 optimisation to pre-clinical organism-level evaluations
                 and beyond to extensive clinical trials assessing
                 effectiveness and safety of new medicines. Machine
                 learning, in particular support vector machines SVM,
                 particle swarm optimisation PSO and genetic programming
                 GP, is increasingly used.",
  abstract =     "Machine learning tools, in particular support vector
                 machines (SVM), Particle Swarm Optimisation (PSO) and
                 Genetic Programming (GP), are increasingly used in
                 pharmaceuticals research and development. They are
                 inherently suitable for use with noisy, high
                 dimensional (many variables) data, as is commonly used
                 in cheminformatic (i.e. In silico screening),
                 bioinformatic (i.e. bio-marker studies, using DNA chip
                 data) and other types of drug research studies. These
                 aspects are demonstrated via review of their current
                 usage and future prospects in context with drug
                 discovery activities.",
  notes =        "http://www.cranfield.ac.uk/wsc10/ broken Original
                 conference title= WSC10: 10th Online World Conference
                 on Soft Computing in Industrial Applications
                 http://isxp1010c.sims.cranfield.ac.uk/Presentations/presentation196.pdf
                 broken slides (1Mbyte)

                 Revised following conference. Published 2006. See
                 link.springer.com for published version",
}

Genetic Programming entries for S J Barrett William B Langdon

Citations