229 citations · 294 across the 4 of their papers we have counts for
4 papers
Investigating Data Pruning for Pretraining Biological Foundation Models at Scale
Yifan Wu, Jiyue Jiang, Xichen Ye +9
Biological foundation models (BioFMs), pretrained on large-scale biological sequences, have recently shown strong potential in providing meaningful representations for diverse down…
Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment Generation
Le Zhang, Jiayang Chen, Tao Shen +2
The field of protein folding research has been greatly advanced by deep learning methods, with AlphaFold2 (AF2) demonstrating exceptional performance and atomic-level precision. As…
Accurate RNA 3D structure prediction using a language model-based deep learning approach
Tao Shen, Zhihang Hu, Siqi Sun +14
Accurate prediction of RNA three-dimensional (3D) structure remains an unsolved challenge. Determining RNA 3D structures is crucial for understanding their functions and informing…
Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions
Jiayang Chen, Zhihang Hu, Siqi Sun +9
Non-coding RNA structure and function are essential to understanding various biological processes, such as cell signaling, gene expression, and post-transcriptional regulations. Th…