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    Events: CfP: Workshop on Data Mining in Drug Discovery
    Submitted by Huzefa Rangwala; posted on Monday, December 01, 2008 (1 comment)

    Submitter

    1st International Workshop on Data Mining in Drug Discovery (RxDM, held in conjunction with SIAM Data Mining Conference (SDM 2009))

    LOCALE: Sparks, NV, USA
    DATES: April 30-May 2, 2009

    There is a need for mapping the different spaces "biological" with "chemical" to understand the function of complex biological systems, with implications in drug discovery. We urge researchers in data mining to participate in this unique workshop by submitting a paper.

    Suggested topics (but not limited to the following) include: Structure-Activity Relationship Models; Chemical Descriptor Spaces; Predictive Toxicology; Gene, Disease, Drug Connections; Chemical Genetics and Chemogenomics; Structural Bioinformatics; Systems Biology and Drugs; and Network Pharmacology.

    FOR MORE INFORMATION

    www.cs.gmu.edu/~hrangwal/rxdm

    Contact Workshop Chairs at rangwala AT CS DOT GMU DOT EDU for questions.

    Expanded view | Monitor forum | Save place

    Reminds me of SCOL :D
    Submitted by Dan Bolser; posted on Wednesday, December 03, 2008
    SCOL : The Structural Classification of Ligands http://www.bioinformatics.org/scol/ The objective of the SCOL project is to produce a global hierarchical clustering of all the available small molecules and protein ligands using measures of structural, chemical and biological 'similarity' between molecules. At a broad level, this hierarchical classification should reflect biological and chemical intuitions about the major classes of molecule and their broad physical and chemical characteristics. At a more detailed level of classification, structurally and chemically similar molecules should be grouped together. This classification system should prove useful for diverse studies, from the gross assessment of metabolic evolution to ligand binding studies. The ultimate aim is to assist in the process of drug discovery and lead compound identification. A distinct sub project of SCOL is the derivation of a set of 'representative' or 'non-redundant' compounds for input into more detailed structural and functional studies.
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