Elucidating the Utility of Genomic Elements with Neural Nets
EUGENe is a Python toolkit for building and evaluating sequence-based deep learning models in genomics. It provides a unified workflow for managing data, training models, and interpreting predictions on biological sequences.
You can find the current documentation here for getting started.
If you use EUGENe for your research, please cite our preprint: Klie et al. bioRxiv 2022
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Release files for eugene-tools 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| eugene_tools-0.1.2.tar.gz | 80.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| eugene_tools-0.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 187.2 kB
Release files / eugene_tools-0.1.2.tar.gz
| Download URL | eugene_tools-0.1.2.tar.gz |
|---|---|
| Size | 80.3 kB |
| Tags | Source |
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Release files / eugene_tools-0.1.2-py3-none-any.whl
| Download URL | eugene_tools-0.1.2-py3-none-any.whl |
|---|---|
| Size | 107.0 kB |
| Tags | Python 3 |
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