Interpretable machine learning system for discovering hidden regulatory switches in non-coding DNA using ENCODE genomic data. Optimized for resource-constrained, reproducible research.

5 stars 3 forks 5 watchers Jupyter Notebook MIT License
bioinformatics computational-biology data-science deep-learning dna encode epigenomics explainable-ai genomics machine-learning mlops neural-networks non-coding-dna python regulatory-genomics reproducible-research
2 Open Issues Need Help Last updated: Jul 30, 2026

Open Issues Need Help

View All on GitHub

Interpretable machine learning system for discovering hidden regulatory switches in non-coding DNA using ENCODE genomic data. Optimized for resource-constrained, reproducible research.

Jupyter Notebook
#bioinformatics#computational-biology#data-science#deep-learning#dna#encode#epigenomics#explainable-ai#genomics#machine-learning#mlops#neural-networks#non-coding-dna#python#regulatory-genomics#reproducible-research
enhancement help wanted phase-2 experiment

Interpretable machine learning system for discovering hidden regulatory switches in non-coding DNA using ENCODE genomic data. Optimized for resource-constrained, reproducible research.

Jupyter Notebook
#bioinformatics#computational-biology#data-science#deep-learning#dna#encode#epigenomics#explainable-ai#genomics#machine-learning#mlops#neural-networks#non-coding-dna#python#regulatory-genomics#reproducible-research