alterlab-molfeat
SolidFeaturizes molecules for machine learning with molfeat (100+ featurizers) — ECFP and MACCS fingerprints, physicochemical descriptors, and pretrained model embeddings (ChemBERTa), converting SMILES into feature vectors. Use when turning molecules into ML-ready features for QSAR or molecular modeling, or comparing fingerprint and descriptor representations. Part of the AlterLab Academic Skills suite.
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Quality Score: 87/100
Skill Content
Details
- Author
- AlterLab-IEU
- Repository
- AlterLab-IEU/AlterLab-Academic-Skills
- Created
- 2 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
molfeat
Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.
molfeat
Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.
molfeat
Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.