WeiminWu2000/Genome_Factory

An Integrated Library for Tuning, Deploying and Interpreting Genomic Models

22
/ 100
Experimental

This tool helps computational biologists and genomic researchers fine-tune and use advanced genomic AI models. You can input raw genomic sequences from public databases like NCBI or your own CSV files, apply various processing steps, and then train powerful models like DNABERT-2 or HyenaDNA. The output includes trained models, extracted embeddings, and generated sequences, along with interpretable insights into model predictions.

123 stars. No commits in the last 6 months.

Use this if you are a computational biologist or genomic researcher looking to apply state-of-the-art AI models to analyze genomic sequences for classification, regression, or sequence generation tasks.

Not ideal if you are new to genomic data analysis or machine learning and prefer a graphical user interface or have very small-scale, simple sequence analysis needs.

genomics computational-biology genome-analysis bioinformatics genomic-modeling
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 2 / 25

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Stars

123

Forks

1

Language

Python

License

Last pushed

Sep 20, 2025

Commits (30d)

0

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