229 citations · 331 across the 9 of their papers we have counts for
9 papers
MOLAR: Learning Multimodal Molecular Representations from Noisy Labels
Yingxu Wang, Kunyu Zhang, Nan Yin +2
Motivation: Noisy labels are a common challenge in molecular property prediction because molecular annotations are often obtained from assays, curated databases, or weak annotation…
Unbiased organism-agnostic and highly sensitive signal peptide predictor with deep protein language model
Junbo Shen, Qinze Yu, Shenyang Chen +3
Signal peptide (SP) is a short peptide located in the N-terminus of proteins. It is essential to target and transfer transmembrane and secreted proteins to correct positions. Compa…
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…
Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration
Xuesong Wang, Zhihang Hu, Tingyang Yu +5
Muilti-modality data are ubiquitous in biology, especially that we have entered the multi-omics era, when we can measure the same biological object (cell) from different aspects (o…
CLMB: deep contrastive learning for robust metagenomic binning
Pengfei Zhang, Zhengyuan Jiang, Yixuan Wang +1
The reconstruction of microbial genomes from large metagenomic datasets is a critical procedure for finding uncultivated microbial populations and defining their microbial function…
HMD-AMP: Protein Language-Powered Hierarchical Multi-label Deep Forest for Annotating Antimicrobial Peptides
Qinze Yu, Zhihang Dong, Xingyu Fan +2
Identifying the targets of an antimicrobial peptide is a fundamental step in studying the innate immune response and combating antibiotic resistance, and more broadly, precision me…
Protein-RNA interaction prediction with deep learning: Structure matters
Junkang Wei, Siyuan Chen, Licheng Zong +2
Protein-RNA interactions are of vital importance to a variety of cellular activities. Both experimental and computational techniques have been developed to study the interactions.…