Saprothub: Making protein modeling accessible to all biologists

J Su, Z Li, C Han, Y Zhou, Y He, J Shan, X Zhou… - bioRxiv, 2024 - biorxiv.org
Training and deploying deep learning models pose challenges for users without machine
learning (ML) expertise. SaprotHub offers a user-friendly platform that democratizes the …

A Survey of Quantized Graph Representation Learning: Connecting Graph Structures with Large Language Models

Q Lin, Z Peng, K Shi, K He, Y Xu, E Cambria… - arxiv preprint arxiv …, 2025 - arxiv.org
Recent years have witnessed rapid advances in graph representation learning, with the
continuous embedding approach emerging as the dominant paradigm. However, such …

Bio2Token: All-atom tokenization of any biomolecular structure with Mamba

A Liu, A Elaldi, N Russell, O Viessmann - arxiv preprint arxiv:2410.19110, 2024 - arxiv.org
Efficient encoding and representation of large 3D molecular structures with high fidelity is
critical for biomolecular design applications. Despite this, many representation learning …

Tokenized and Continuous Embedding Compressions of Protein Sequence and Structure

AX Lu, W Yan, KK Yang, V Gligorijevic, K Cho… - bioRxiv, 2024 - biorxiv.org
Existing protein machine learning representations typically model either the sequence or
structure distribution, with the other modality implicit. The latent space of sequence-to …