Results for “pharmaceutical”
8 skillsMore results
lingxling medchem
Filters and prioritizes compound libraries in drug discovery using drug-likeness rules, structural alerts, complexity metrics, and a query language.
253 · bundle
lingxling pytdc
Access AI-ready drug discovery datasets, benchmarks, and molecular oracles from Therapeutics Data Commons for therapeutic machine learning and pharmacological prediction.
253 · bundle
k-dense-ai medchem
Apply medicinal chemistry filters for compound triage: drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and a custom query language for library filtering.
30.2k · bundle
k-dense-ai pytdc
Access AI-ready drug discovery datasets and benchmarks from Therapeutics Data Commons, covering ADME, toxicity, drug-target interactions, and molecular generation with standardized splits and evaluation metrics.
30.2k · bundle
k-dense-ai deepchem
Predict molecular properties, train graph neural networks, and run drug discovery workflows using DeepChem's featurizers, models, and MoleculeNet benchmarks.
30.2k · bundle
k-dense-ai torchdrug
Build and train graph neural networks for drug discovery, protein modeling, and molecular science using PyTorch-native tools.
30.2k · bundle
lingxling datamol
Pythonic wrapper around RDKit for cheminformatics, simplifying SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, and parallel processing while returning native rdkit.Chem.Mol objects.
253 · bundle