This is a group project developed by Xin, Stanley, Nabila, and Zixian for BIL 652 at University of Miami. Our project focuses on gene function annotation from nucleotide sequences using bioinformatics pipelines.
This bioinformatics tool takes raw nucleotide sequences in .fna format as input and performs functional annotation to identify gene characteristics and associated biological functions.
It is designed for researchers and students needing a simple, reproducible workflow to parse and analyze gene sequences. The project uses a Jupyter Notebook pipeline accessible via Google Colab.
Click the badge below to open the notebook in Google Colab:
Bioinformatics_Too_Indecisive/
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├── LICENSE
├── README.md
├── .github/
└── workflows/
└── pages.yml
├── example
└── sequences.fna
└── outputs/
└── alignments/
└── organism_origin/
└── phylogenetic_tree/
└── sequence_properties/
├── notebooks/
└── Group_2_(Too_indecisive)_.ipynb
└── results/
├── docs/
└── index.md (GitHub Pages site)
└── acknowledgements.md
└── _config.yml
└── Gemfile
└── tutorial/
└── index.md
- File format:
.fna— FASTA format nucleotide sequences - Example file:
sequences.fna - This file contains concatenated gene sequences for functional analysis.
- Functionally annotated genes with:
- Predicted gene functions
- Sequence features and possible biological roles
- Intermediate parsing and processing steps shown in the notebook
- Clone the repository or open the notebook on Google Colab.
- Upload your
.fnafile when prompted. - Follow the step-by-step instructions inside the notebook.
- View and interpret the functional annotations from the output.
This project is licensed under the MIT License.
Feel free to fork, modify, and submit pull requests. This tool is part of an educational assignment, and we welcome suggestions for improving usability and functionality.
If you use this tool in your research or coursework, please cite this repository and the University of Miami BIL 652 course.