Asset Detail:
Cancer Kinase Selectivity
Asset Detail:
Cancer Kinase Selectivity
Overview
| ASSET LINK: | https://modac.cancer.gov/assetDetails?dme_data_id=NCI-DME-MS01-8091812 |
| PROGRAM NAME: | Accelerating Therapeutics for Opportunities in Medicine (ATOM) |
| STUDY NAME: | Disease Target Identification |
| ASSET NAME: | Cancer Kinase Selectivity |
| ASSET PATH: | /NCI_DOE_Archive/ATOM/disease_target_identification/Cancer_Kinase_Selectivity |
Asset Attributes
| ATTRIBUTE | VALUE |
|---|---|
| ASSET NAME | Cancer Kinase Selectivity |
| ASSET DESCRIPTION | This asset contains datasets and models for disease target identification. The datasets 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. Anyone can reuse the machine learning models to evaluate small-molecule compound potency against selected kinase targets. |
| ASSET IDENTIFIER | Cancer_Kinase_Selectivity |
| ASSET TYPE | Model |
| MODEL DOMAIN | Cancer treatments |
| MODEL FRAMEWORK | Scikit-learn |
| MODEL PLATFORM | AMPL |
| PLATFORM VERSION | 1.1.0 |
| POC NAME | Hiranmayi Ranganathan, Jonathan Allen |
| POC EMAIL | allen99@llnl.gov; ranganathan2@llnl.gov |
| IS MODEL DEPLOYED | No |
| COLLECTION SIZE | 24.3 MB |
| GITHUB LINK | https://github.com/ATOMconsortium/AMPL |
Asset Files
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| FILE/COLLECTION | FILE SIZE | ACTIONS |
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