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Machine Learning Models for Predicting Kinase Inhibitors with Different Binding Modes

Miljković, Filip; Rodríguez-Pérez, Raquel; Bajorath, Jürgen


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    "description": "<p>Random forest (RF), support-vector machine (SVM), and deep neural network (DNN) models for predicting kinase inhibitors with different binding modes in X-ray structures are made available together with the data sets used for training and testing.</p>\n\n<p>Please refer to READ_ME.txt for more information.</p>", 
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    "title": "Machine Learning Models for Predicting Kinase Inhibitors with Different Binding Modes", 
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    "keywords": [
      "protein kinases", 
      "kinase inhibitors", 
      "machine learning", 
      "inhibitor binding modes", 
      "classification models", 
      "X-ray data"
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    "publication_date": "2019-08-18", 
    "creators": [
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        "affiliation": "Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universit\u00e4t, Endenicher Allee 19c, D-53115 Bonn, Germany.", 
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        "name": "Rodr\u00edguez-P\u00e9rez, Raquel"
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