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The Cancer Kinase Selectivity resource contains datasets and models for disease target identification.
Enables disease target identification.
The Cancer Kinase Selectivity model and components include raw data from DTC, ChEMBL and ExCAPE-DB databases along with the Union train/test set data. The corresponding Union models had been trained on the AURKA union training set and the AURKB union training set with ATOMs open-source AMPL software.
Provides Union models that have been trained on the AURKA union training set.
Data scientists can reuse the machine learning models to evaluate small-molecule compound potency against selected kinase targets.
The components are located in the Model and Data Clearinghouse (MoDaC) for datasets and compiled model with Github for source code.
This will be added as available.