https://github.com/dhslab/epibench
EpiBench is a software tool designed for predicting DNA methylation levels using genomic sequence data and histone modification marks. It employs a multi-branch CNN architecture tailored for integrating these data types to achieve high prediction accuracy.
Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
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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 links in README
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (1.8%) to scientific vocabulary
Last synced: 4 months ago
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JSON representation
Repository
EpiBench is a software tool designed for predicting DNA methylation levels using genomic sequence data and histone modification marks. It employs a multi-branch CNN architecture tailored for integrating these data types to achieve high prediction accuracy.
Basic Info
- Host: GitHub
- Owner: dhslab
- License: mit
- Language: Python
- Default Branch: main
- Size: 270 MB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Created 10 months ago
· Last pushed 8 months ago
Metadata Files
Readme
License
Owner
- Name: Code and Software from David Spencer's lab
- Login: dhslab
- Kind: organization
- Email: dspencerlab@gmail.com
- Location: United States of America
- Website: davidspencerlab.org
- Twitter: dspencerlab
- Repositories: 6
- Profile: https://github.com/dhslab
GitHub Events
Total
- Push event: 6
Last Year
- Push event: 6
Dependencies
package-lock.json
npm
- 260 dependencies
package.json
npm
- @anthropic-ai/sdk ^0.39.0
- boxen ^8.0.1
- chalk ^4.1.2
- cli-table3 ^0.6.5
- commander ^11.1.0
- cors ^2.8.5
- dotenv ^16.3.1
- express ^4.21.2
- fastmcp ^1.20.5
- figlet ^1.8.0
- fuse.js ^7.0.0
- gradient-string ^3.0.0
- helmet ^8.1.0
- inquirer ^12.5.0
- jsonwebtoken ^9.0.2
- lru-cache ^10.2.0
- openai ^4.89.0
- ora ^8.2.0
requirements.txt
pypi
- argparse >=1.4.0
- biopython >=1.79
- captum >=0.5.0
- h5py >=3.1.0
- joblib >=1.1.0
- jupyter >=1.0.0
- matplotlib >=3.4.0
- numpy >=1.21.0
- optuna >=3.0.0
- pandas >=1.3.0
- plotly >=5.3.0
- pyBigWig >=0.3.18
- pyfaidx >=0.6.4
- pyyaml >=6.0
- scikit-learn >=1.0.0
- scipy >=1.7.0
- seaborn >=0.11.0
- shap >=0.40.0
- statsmodels >=0.13.0
- torch >=1.12.0
- tqdm >=4.62.0
setup.py
pypi
- argparse >=1.4.0
- biopython >=1.79
- captum >=0.5.0
- h5py >=3.1.0
- joblib >=1.1.0
- jupyter >=1.0.0
- matplotlib >=3.4.0
- numpy >=1.21.0
- optuna >=3.0.0
- pandas >=1.3.0
- plotly >=5.3.0
- pyBigWig >=0.3.18
- pyfaidx >=0.6.4
- pyyaml >=6.0
- scikit-learn >=1.0.0
- scipy >=1.7.0
- seaborn >=0.11.0
- shap >=0.40.0
- statsmodels >=0.13.0
- torch >=1.12.0
- tqdm >=4.62.0