ml-jku / clamp
Code for the paper Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language
Why this job: works in the areas we cover, but does not say which job it does
What it does
CLAMP (Contrastive Language-Assay Molecule Pre-Training) is trained on molecule-bioassay pairs. It can be instructed in natural language to predict the most relevant molecule, given a textual description of a bioassay, without training samples. In extensive experiments, our method yields improved predictive performance on few-shot learning benchmarks and zero-shot problems in drug discovery.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Inactive
- Last commit 8 months ago
- Stars
- 121
- On GitHub
- Licence
- Custom
- Read before business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 82% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 90% closed
- 1 still open
- Pull requests
- 1 merged
- 0 waiting
- Releases
- None
- Never published
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Python 82%
- Jupyter Notebook 18%
Topics
- assay-modeling
- cheminformatics
- contrastive-learning
- drug-discovery
- machine-learning
- qsar
- zero-shot
Project record
- JobOther AI tools
- StatusListed
- Commits39
- Forks10
- Watching5
- Stars in 28 days0
- CreatedJan 22, 2023
- First seen by usNov 7, 2026
- CheckedNov 8, 2026