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

  • S. J. Barrett
  • W. B. Langdon
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 36)

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.

Keywords

Support Vector Machine Particle Swarm Optimiza Feature Selection Particle Swarm Drug Discovery 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • S. J. Barrett
    • 1
  • W. B. Langdon
    • 2
  1. 1.Analysis Applications, Research and TechnologiesGlaxoSmithKline R&DGreenford, MiddlesexUK
  2. 2.Computer ScienceUniversity of EssexColchesterUK

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