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torchdrug

PyTorch-native graph neural networks for molecules and proteins. Use when building custom GNN architectures for drug discovery, protein modeling, or knowledge graph reasoning. Best for custom model development, protein property prediction, retrosynthesis. For pre-trained models and diverse featurizers use deepchem; for benchmark datasets use pytdc.

82

1.28x
Quality

75%

Does it follow best practices?

Impact

98%

1.28x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/pharma/torchdrug/SKILL.md
SKILL.md
Quality
Evals
Security

Evaluation results

98%

18%

Automated Synthesis Route Prediction

Retrosynthesis two-stage pipeline

Criteria
Without this skill
With this skill

USPTO50k dataset

100%

100%

RGCN for center identification

100%

100%

GIN for synthon completion

0%

100%

CenterIdentification task

100%

100%

SynthonCompletion task

100%

100%

num_bond_type for RGCN

100%

100%

Two separate models

100%

100%

node_feature_dim from dataset

100%

100%

uv pip install

0%

0%

top_k for center identification

0%

100%

98%

Biomedical Knowledge Graph Drug Repurposing

Knowledge graph completion for drug repurposing

Criteria
Without this skill
With this skill

RotatE or ComplEx model

100%

100%

Hetionet dataset

100%

100%

KnowledgeGraphCompletion task

100%

100%

adversarial_temperature param

100%

100%

num_negative param

100%

100%

num_entity from dataset

100%

100%

num_relation from dataset

100%

100%

BCE criterion for KG

100%

100%

uv pip install

0%

0%

Compound-disease query

100%

100%

100%

36%

CNS Drug Candidate Screening Pipeline

Molecular GNN model selection and training

Criteria
Without this skill
With this skill

GIN model choice

100%

100%

Scaffold split

0%

100%

Node feature dim from dataset

0%

100%

Edge feature dim from dataset

0%

100%

Batch norm enabled

100%

100%

BCE criterion

100%

100%

AUROC metric

100%

100%

AUPRC metric

100%

100%

PropertyPrediction task

100%

100%

uv pip install

0%

100%

Repository
wu-yc/LabClaw
Evaluated
Agent
Claude Code
Model
Claude Sonnet 4.6

Table of Contents

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