https://github.com/bytedance/markov-molecular-sampling
Science Score: 36.0%
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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✓Committers with academic emails
1 of 1 committers (100.0%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (6.8%) to scientific vocabulary
Keywords
Repository
Basic Info
Statistics
- Stars: 54
- Watchers: 4
- Forks: 13
- Open Issues: 2
- Releases: 0
Topics
Metadata Files
README.md
MARS: Markov Molecular Sampling for Multi-objective Drug Discovery
Thanks for your interest! This is the code repository for our ICLR 2021 paper MARS: Markov Molecular Sampling for Multi-objective Drug Discovery.
Dependencies
The conda environment is exported as environment.yml. You can also manually install these packages:
```bash conda install -c conda-forge rdkit conda install tqdm tensorboard scikit-learn conda install pytorch cudatoolkit=11.1 -c pytorch -c conda-forge conda install -c dglteam dgl-cuda11.1
for cpu only
conda install pytorch cpuonly -c pytorch conda install -c dglteam dgl ```
Run
Note: Run the commands outside the
MARSdirectory.
To extract molecular fragments from a database:
bash
python -m MARS.datasets.prepro_vocab
To sample molecules:
bash
python -m MARS.main --train --run_dir runs/RUN_DIR
Evaluation and Generated Molecules
The generated molecules are evaluated at each step and the results are stored in runs/RUN_DIR (runs/debug by default). Please refer to tensorboard files for the evaluation results and mols.txt for all the molecules generated during sampling.
The experiment results we listed in the paper are obtained by averaging the outcomes of 10 independent sampling paths. For each sampling path, we record the evaluation results of the step that produces the highest PM score.
Citation
@inproceedings{
xie2021mars,
title={MARS: Markov Molecular Sampling for Multi-objective Drug Discovery},
author={Yutong Xie and Chence Shi and Hao Zhou and Yuwei Yang and Weinan Zhang and Yong Yu and Lei Li},
booktitle={International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=kHSu4ebxFXY}
}
Owner
- Name: Bytedance Inc.
- Login: bytedance
- Kind: organization
- Location: Singapore
- Website: https://opensource.bytedance.com
- Twitter: ByteDanceOSS
- Repositories: 255
- Profile: https://github.com/bytedance
GitHub Events
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- Watch event: 9
Last Year
- Watch event: 9
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Last synced: about 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| yuweiy | y****4@n****u | 2 |
Committer Domains (Top 20 + Academic)
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Last synced: about 1 year ago
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Top Authors
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- 1200Caixia (1)
- TryLittleHarder (1)