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Machine learning and screening data

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Chemogenomics and Chemical Genetics

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Abstract

In all living beings, to differing degrees and with the help of extremely varying mechanisms (genetic, chemical or cultural), one observes an aptitude for acquiring new behaviour through their interaction with the environment. The objective of machine learning is to study and put into effect such mechanisms using artificial systems: robots, computers etc.

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Author information

Authors and Affiliations

  1. Grenoble Institute of Applied Mathematics, TIMC IMAG Laboratory - Joseph Fourier University, Grenoble, France

    Gilles Bisson (Research officer, CNRS)

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  1. Gilles Bisson
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Editors and Affiliations

  1. UMR 5168 CNRS CEA INRA UNIV JF, Joseph Fourier University, Rue des Martyrs 17, 38054 Grenoble Cedex 9, France

    ERIC MARECHAL

  2. Institute of Life Sciences Research and, Lab. of Plant Cell Physiology, CNRS-CEA-INRA, Joseph Fourier University, Grenoble, France

    Sylvaine Roy

  3. Department of Cellular Differentiation a, Albert Bonniot Institute, Rond-point de la Chantourne, La Tronche Cedex, 38706, France

    Laurence Lafanechère

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Bisson, G. (2011). Machine learning and screening data. In: MARECHAL, E., Roy, S., Lafanechère, L. (eds) Chemogenomics and Chemical Genetics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19615-7_15

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