Query PharmGKB and CPIC for drug-gene interactions, pharmacogenomic annotations, and dosing guidelines. Use when predict…
FreedomIntelligence/OpenClaw-Medical-Skills查看
数据与复现
DE
DeepChem
维护者 K-Dense Inc. · 最近更新 2026年4月1日
DeepChem is a comprehensive Python library for applying machine learning to chemistry, materials science, and biology. Enable molecular property prediction, drug discovery, materials design, and biomolecule analysis through speciali.
原始来源
K-Dense-AI/claude-scientific-skills
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/deepchem
- 维护者
- K-Dense Inc.
- 许可
- MIT license
- 最近更新
- 2026年4月1日
技能摘要
来自 SKILL.md 的关键信息
核心说明
- DeepChem是一个comprehensive Python 库 ，用于 applying 机器学习 to chemistry，材料科学，、 biology. Enable molecular property prediction，drug discovery，materials design，、 biomolecule analysis through specialized neural networks，molecular featurization methods，、 pretrained models。
- featurizer = dc.feat.CircularFingerprint(radius=2，size=2048) loader = dc.data.CSVLoader( tasks=['solubility'，'toxicity']，feature_field='smiles'，featurizer=featurizer ) 数据集 = loader.create_数据集('molecules.csv')。
原始文档
SKILL.md 摘录
When to Use This Skill
This skill should be used when:
- Loading and processing molecular data (SMILES strings, SDF files, protein sequences)
- Predicting molecular properties (solubility, toxicity, binding affinity, ADMET properties)
- Training models on chemical/biological datasets
- Using MoleculeNet benchmark datasets (Tox21, BBBP, Delaney, etc.)
- Converting molecules to ML-ready features (fingerprints, graph representations, descriptors)
- Implementing graph neural networks for molecules (GCN, GAT, MPNN, AttentiveFP)
- Applying transfer learning with pretrained models (ChemBERTa, GROVER, MolFormer)
- Predicting crystal/materials properties (bandgap, formation energy)
- Analyzing protein or DNA sequences
1. Molecular Data Loading and Processing
DeepChem provides specialized loaders for various chemical data formats:
import deepchem as dc
## Load SDF files
loader = dc.data.SDFLoader(tasks=['activity'], featurizer=featurizer)
dataset = loader.create_dataset('compounds.sdf')
适用场景
- Loading 、 processing molecular data (SMILES strings，SDF files，protein sequences)。
- Predicting molecular properties (solubility，toxicity，binding affinity，ADMET properties)。
- Training models on chemical/biological 数据集s。
- 使用 MoleculeNet benchmark 数据集s (Tox21，BBBP，Delaney，etc.)。
不适用场景
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
相关技能
相关技能
CH
CheMatAgent: chemistry-aware drug design with retrosynthesis and property optimization.
FreedomIntelligence/OpenClaw-Medical-Skills查看
CH
数据与复现
ChEMBL
ChEMBL is a manually curated database of bioactive molecules maintained by the European Bioinformatics Institute (EBI),…
K-Dense-AI/claude-scientific-skills查看
CH
ChemCrow drug discovery toolkit: web search, Python, chemical tools integration.
FreedomIntelligence/OpenClaw-Medical-Skills查看