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The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F15%3A10312095" target="_blank" >RIV/00216208:11320/15:10312095 - isvavai.cz</a>

  • Result on the web

    <a href="http://siret.ms.mff.cuni.cz/p2rank" target="_blank" >http://siret.ms.mff.cuni.cz/p2rank</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    P2RANK

  • Original language description

    P2RANK is a novel machine learning-based method for prediction of ligand binding sites from protein structure. P2RANK uses Random Forests classifier to infer ligandability of local chemical neighborhoods near the protein surface which are represented byspecific near-surface points and described by aggregating physico-chemical features projected on those points from neighboring protein atoms. The points with high predicted ligandability are clustered and ranked to obtain the resulting list of binding site predictions.

  • Czech name

  • Czech description

Classification

  • Type

    R - Software

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GP14-29032P" target="_blank" >GP14-29032P: Efficient chemical space exploration using multi-objective optimization</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Internal product ID

    prank_2.0

  • Technical parameters

    stand-alone konzolová aplikace

  • Economical parameters

    Free academic software

  • Owner IČO

    00216208

  • Owner name

    Univerzita Karlova v Praze