RNA-FM

This repository contains codes and pre-trained models for RNA foundation model (RNA-FM). RNA-FM outperforms all tested single-sequence RNA language models across a variety of structure prediction tasks as well as several function-related tasks. You can find more details about RNA-FM in our paper, "Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions" (Chen et al., 2022).

Overview

If you find the models useful in your research, we ask that you cite the relevant paper:

For RNA-FM:

@article{chen2022interpretable,
  title={Interpretable rna foundation model from unannotated data for highly accurate rna structure and function predictions},
  author={Chen, Jiayang and Hu, Zhihang and Sun, Siqi and Tan, Qingxiong and Wang, Yixuan and Yu, Qinze and Zong, Licheng and Hong, Liang and Xiao, Jin and King, Irwin and others},
  journal={arXiv preprint arXiv:2204.00300},
  year={2022}
}
  

The model of this code builds on the esm sequence modeling framework. And we use fairseq sequence modeling framework to train our RNA language modeling. We very appreciate these two excellent works!