---
license: mit
task_categories:
- text-generation
tags:
- protein-sequence-generation
- bioinformatics
- pfam
- ancestral-sequence-reconstruction
- protein-family
---

# LineageFlow Pfam Assets

This dataset contains the preprocessed Pfam assets used by the released LineageFlow inference pipeline, as presented in the paper [LineageFlow: Flow Matching for High-Fidelity Family-Aware Protein Sequence Generation](https://huggingface.co/papers/2605.22252).

**Resources:**
- **Paper:** [https://huggingface.co/papers/2605.22252](https://huggingface.co/papers/2605.22252)
- **GitHub:** [https://github.com/Jinx-byebye/LineageFlow](https://github.com/Jinx-byebye/LineageFlow)

## Contents

- `pfam_priors_asr_mad/`: family-specific ASR Dirichlet priors.
- `pfam_gap_rates/`: family-specific alignment gap statistics.
- `pfam_fastas_clean/`: cleaned Pfam family alignments.
- `pfam_pi_smooth_tau0.5_gap060_gt80_020.csv`: family sampling distribution.
- `pfam_priors_keep_ids_gap060_gt80_020.txt`: family keep list used by the default sampler.

## Usage

You can download the preprocessed Pfam assets using the Hugging Face CLI:

```bash
hf download jinxbye/LineageFlow-assets \
  --repo-type dataset \
  --local-dir dataset
```

The inference scripts in the GitHub repository expect these assets under `dataset/` by default. All paths can be overridden from the command line.

## Citation

```bibtex
@inproceedings{liang2026lineageflow,
  title     = {LineageFlow: Flow Matching for High-Fidelity Family-Aware Protein Sequence Generation},
  author    = {Liang, Langzhang and Yang, Ming and Feng, Yi and Li, Junfan and Pan, Shirui and Xu, Yinghui and Ying, Tianlei and Zheng, Yizhen and Xu, Zenglin},
  booktitle = {Proceedings of the 43rd International Conference on Machine Learning},
  year      = {2026}
}
```

## Notes

These files are preprocessed from Pfam family alignments. Please follow the license and usage terms of the original Pfam resource when using the data.