nf-core/deepmodeloptim
Stochastic Testing and Input Manipulation for Unbiased Learning Systems
This project helps biological researchers and data scientists working with deep learning models to improve their model performance. It takes your raw biological data (like DNA sequences or RNA sequencing results) and your PyTorch deep learning model as input. The project then strategically enhances your training data, leading to a more robust and accurate model output by identifying an optimal task-specific training set.
Use this if you are developing deep learning models for biological applications and want to systematically augment your training data to achieve better, less biased model performance.
Not ideal if you are not working with biological data, or if you prefer to manually curate and augment your training datasets without an automated pipeline.
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30
Forks
14
Language
Nextflow
License
MIT
Category
Last pushed
Nov 20, 2025
Commits (30d)
0
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