Asset Detail:
QMugs HOMO-LUMO Prediction Model
Asset Detail:
QMugs HOMO-LUMO Prediction Model
Overview
| ASSET LINK: | https://modac.cancer.gov/assetDetails?dme_data_id=NCI-DME-MS01-63856556 |
| PROGRAM NAME: | Accelerating Therapeutics for Opportunities in Medicine (ATOM) |
| STUDY NAME: | QMugs HOMO-LUMO Gap Prediction |
| ASSET NAME: | QMugs HOMO-LUMO Prediction Model |
| ASSET PATH: | /NCI_DOE_Archive/ATOM/QMugs/QMugs_HOMO-LUMO_Prediction_Model |
Asset Attributes
| ATTRIBUTE | VALUE |
|---|---|
| ASSET NAME | QMugs HOMO-LUMO Prediction Model |
| ASSET DESCRIPTION | A neural network model that predicts the HOMO-LUMO gap of a molecule, given its standardized smile string. This model was trained using the curated quantum mechanical properties of drug-like molecules (QMugs) dataset. |
| ASSET IDENTIFIER | QMugs_HOMO-LUMO_Prediction_Model |
| ASSET TYPE | Model |
| DOI | https://doi.org/10.1038/s41597-022-01390-7 |
| MODEL DOMAIN | Chemical Property Prediction |
| MODEL FRAMEWORK | PyTorch |
| MODEL PLATFORM | AMPL |
| PLATFORM VERSION | None |
| POC NAME | Thangavelu, Chloe |
| POC EMAIL | cthangav@uci.edu |
| IS MODEL DEPLOYED | Yes |
| COLLECTION SIZE | 140.7 MB |
Asset Files
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| FILE/COLLECTION | FILE SIZE | ACTIONS |
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