| | --- |
| | license: mit |
| | --- |
| | |
| | # BarcodeMamba for Taxonomic Classification |
| |
|
| | A performant and efficient Mamba-2-based foundation model for DNA barcodes in biodiversity analysis. |
| |
|
| | - Check out our [paper](https://openreview.net/forum?id=6ohFEFTr10) |
| | - Check out our [poster](https://neurips.cc/media/PosterPDFs/NeurIPS%202024/105938.png) |
| |
|
| | # Usage |
| | The pretrained models can be used for both taxonomic classification on seen species (fine-tune & linear probe) and making genus-level predictions on unseen species (1-NN probe). The instructions for using our models can be found at our [GitHub repository](https://github.com/bioscan-ml/BarcodeMamba). |
| |
|
| | # Citation |
| |
|
| | If you find BarcodeMamba useful, please consider citing: |
| |
|
| | ``` |
| | @inproceedings{ |
| | gao2024barcodemamba, |
| | title={BarcodeMamba: State Space Models for Biodiversity Analysis}, |
| | author={Tiancheng Gao and Graham W.~Taylor}, |
| | booktitle={{NeurIPS} 2024 Workshop on Foundation Models for Science: Progress, Opportunities, and Challenges}, |
| | year={2024}, |
| | url={https://openreview.net/forum?id=6ohFEFTr10} |
| | } |
| | ``` |
| |
|
