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Information Technology Journal
  Year: 2007 | Volume: 6 | Issue: 5 | Page No.: 718-724
DOI: 10.3923/itj.2007.718.724
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Machine Learning Technique Approaches in Drug Discovery, Design and Development

D. Pugazhenthi and S.P. Rajagopalan

Drug discovery refers to the finding of a new drug which could be a completely new compound or a new derivative of existing compounds. Drug discovery is the ultimate goal of drug design which concerned with the design of a chemical compound that exhibits a desired pharmacological activity. 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 data, as is commonly used in cheminformatic, bioinformatics 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.
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  •    The Research of Ear Recognition Based on Gabor Wavelets and Support Vector Machine Classification
  •    The Evolution of Reusable Programs Using Genetic Algorithm
  •    In silico Analysis of Vi Polyssacharide Biosynthesis Protein of Salmonella typhi
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How to cite this article:

D. Pugazhenthi and S.P. Rajagopalan, 2007. Machine Learning Technique Approaches in Drug Discovery, Design and Development. Information Technology Journal, 6: 718-724.

DOI: 10.3923/itj.2007.718.724






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