Software Open Access
Machine Learning Models for Predicting Kinase Inhibitors with Different Binding Modes
Miljković, Filip;
Rodríguez-Pérez, Raquel;
Bajorath, Jürgen
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.
Please refer to READ_ME.txt for more information.
Files
(386.4 MB)
| Name | Size | |
|---|---|---|
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ML_Kinases.zip
md5:981d640862e7c5bb485e30ecfd8fff8d |
386.4 MB | Download |
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| Views | 1,258 | 981 |
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| Unique views | 1,086 | 889 |
| Unique downloads | 392 | 298 |
Indexed in
- Publication date:
- August 18, 2019
- DOI:
-
- Keyword(s):
- protein kinases kinase inhibitors machine learning inhibitor binding modes classification models X-ray data
- License (for files):
- Creative Commons Attribution 4.0 International