bioai-seq 0.0.2

Privacy-first command-line tool for biotech devs and researchers to analyse sequence data.

🧬 bioai-seq

bioai-seq is a lightweight command-line tool for basic biological sequence analysis. It’s part of my journey toward becoming a Bio AI Software Engineer — combining software engineering, biology, and machine learning.

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💻 Local Development & Testing

1. Create and activate a virtual environment

python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

2. Install required build tools

pip install --upgrade pip setuptools build

3. Run the CLI locally

Run the CLI directly:

python3 -m bioai_seq.cli

Or install locally and use as a command:

pip install .
bioseq

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🚀 Deploying to PyPI (Production)

1. Clean previous builds

rm -rf dist build *.egg-info

2. Build the package

python3 -m build

3. Upload to PyPI

pip install --upgrade twine
twine upload dist/*

• Username: __token__
• Password: your API token from https://pypi.org/manage/account/token/

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📦 Installation (User Guide)

pip install bioai-seq

Then run:

bioseq

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🧪 Planned Example Output

✅ Sequence loaded: 1273 amino acids
🧬 Detected: SARS-CoV-2 spike protein (likely variant: Omicron)
🔍 Running ESM-2 embeddings...
🧪 Predicted secondary structure: 40% alpha-helix, 25% beta-sheet
🧬 Mutation sites detected vs reference: 15
📚 Similar sequences:
 - UniProt P0DTC2 (99.7%)
 - UniProt A0A6H2L9T9 (98.9%)
🧠 Summary:
"This sequence appears to be a mutated spike protein, likely from a recent SARS-CoV-2 variant. Multiple substitutions are present in the RBD region."

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🌐 Follow the Journey

This project is part of a broader initiative to define and grow the Bio AI Software Engineer role.

• 🌍 Blog: https://bioaisoftware.engineer
• 🧑‍💻 GitHub: https://github.com/babilonczyk
• 💼 LinkedIn: https://www.linkedin.com/in/jan-piotrzkowski/

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🛠️ License

MIT — free to use, share, and improve.