Bioactivity-aware chemical embeddings for small molecules. Using transfer learning, we have created a fast network that produces embeddings of 1024 features condensing physicochemical as well as bioactivity information The training of the network has been done using the FS-Mol and ChEMBL datasets, and Grover, Mordred and ECFP descriptors
- EOS model ID:
eos2gw4 - Slug:
eosce
- Input:
Compound - Input Shape:
Single - Task:
Representation - Output:
Descriptor - Output Type:
Float - Output Shape:
List - Interpretation: Embedding of 1024 features representing a compound
- Publication
- Source Code
- Ersilia contributor: GemmaTuron
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