Does it support transfer learning?

Yes, it provides implementation patterns for fine-tuning pretrained models like ChemBERTa, GROVER, and MolFormer for specific downstream chemical tasks.

What molecular formats does this skill support?

It supports standard chemical formats including SMILES strings, SDF files, FASTA sequences, and PDB structures through DeepChem's specialized loader classes.

Can I use this skill for materials science?

Yes, DeepChem includes tools for predicting crystal and materials properties using specialized models like CGCNN and MEGNet, which this skill helps implement.

Why is ScaffoldSplitter recommended for molecular data?

ScaffoldSplitter ensures that molecules with the same structural core (scaffold) are grouped into the same split, preventing data leakage and providing a more realistic measure of how models generalize to new chemical space.

DeepChem Molecular ML

Name: DeepChem Molecular ML
Author: Activer007

byActiver007

0•

データサイエンスとML

Streamlines molecular machine learning workflows for drug discovery, property prediction, and materials science using the DeepChem library.

This skill empowers developers and researchers to leverage the DeepChem Python library for scientific machine learning tasks within Claude. It provides expert guidance on loading chemical data (SMILES, SDF, FASTA), performing sophisticated featurization like circular fingerprints and graph representations, and implementing state-of-the-art models including Graph Neural Networks (GNNs) and pretrained transformers like ChemBERTa. Designed for tasks ranging from ADMET property prediction to benchmarking on MoleculeNet, it ensures best practices like scaffold-based data splitting to prevent data leakage in chemical datasets.

主な機能

01Molecular featurization (Fingerprints, GNNs, Descriptors)

02Advanced data splitting (Scaffold, Butina, Stratified)

03MoleculeNet benchmark dataset integration

04Transfer learning with pretrained chemical models

050 GitHub stars

06Graph Neural Network implementation (GCN, GAT, MPNN)

ユースケース

01Benchmarking chemical ML models using MoleculeNet datasets

02Predicting ADMET and toxicity properties for drug candidates

03Training graph neural networks on molecular structures

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add activer007/ordinary-claude-skills deepchem

For use in Claude.ai and ChatGPT

Download Skill