README.md

---
tags:
- genomics
- gene-expression-prediction
- multimodal
- biology
- arxiv:2602.21550
library_name: pytorch
datasets:
- xingyusu/GeneExp
---

# Prism

Prism provides pretrained checkpoints for gene expression prediction by integrating genomic sequence and multimodal signals.

This repository is the model release for:

**Extending Sequence Length is Not All You Need: Effective Integration of Multimodal Signals for Gene Expression Prediction** (ICLR 2026)

## Paper

- [Hugging Face Paper Page](https://huggingface.co/papers/2602.21550)
- [arXiv: 2602.21550](https://arxiv.org/abs/2602.21550)

## Model Contents

- Pretrained checkpoints for `K562` and `GM12878`
- Five random seeds for each cell type: `2`, `22`, `222`, `2222`, `22222`

## Dataset

Prism follows the same dataset setting as Seq2Exp (`xingyusu/GeneExp`).

## Quick Start

Download checkpoints:

```bash
pip install huggingface_hub
python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='yangyz1230/Prism', repo_type='model', local_dir='./ckpt')"
```

Run inference with the official code:

```bash
git clone https://github.com/yangzhao1230/Prism
cd Prism
pip install -r requirements.txt
DATA_ROOT=/path/to/data
bash test.sh $DATA_ROOT ./ckpt
```

## Limitations

- Research use only
- Performance may vary across preprocessing settings and seeds
- Not intended for clinical or diagnostic use

## Citation

```bibtex
@inproceedings{
yang2026extending,
title={Extending Sequence Length is Not All You Need: Effective Integration of Multimodal Signals for Gene Expression Prediction},
author={Zhao Yang and Yi Duan and Jiwei Zhu and Ying Ba and Chuan Cao and Bing Su},
booktitle={The Fourteenth International Conference on Learning Representations},
year={2026}
}
```

## Links

- Code: https://github.com/yangzhao1230/Prism
- Model: https://huggingface.co/yangyz1230/Prism