alterlab-torchdrug
alterlab-torchdrug is a Bioinformatics & life sciences skill for AI agents, published by AlterLab-IEU in the AlterLab-Academic-Skills repository on GitHub. Skillspace rates alterlab-torchdrug C (77/100) and it passed the safety scan; the rating is based on static analysis only.
Builds PyTorch-native graph neural networks with TorchDrug for molecules and proteins, exposing custom GNN architectures, task/dataset abstractions, molecular generation, retrosynthesis planning, and knowledge-graph reasoning. Use when developing custom graph model layers, predicting protein properties from sequence or structure, or building retrosynthesis and drug-repurposing pipelines; for ready-made featurizers, MoleculeNet benchmarks, and pre-trained models with less code prefer alterlab-deepchem. Part of the AlterLab Academic Skills suite.
- Grade
- C
- Quality
- 77 / 100
- Safety
- Passed
- GitHub stars
- 43
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- over-broad allowed-tools ('*')
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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