activity
20222026
most citedA Survey on Generative Diffusion Model

67 citations · 70 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2026

RNADyn: A Benchmark for Generating and Understanding RNA Dynamics

Yiming Huang, Lennart Bastian, Hanqun Cao +2

Ribonucleic acid (RNA) functions through conformational changes that are not fully captured by static structures. However, large-scale standardized RNA dynamics data remain limited…

cs.AI2025

Lost in Tokenization: Context as the Key to Unlocking Biomolecular Understanding in Scientific LLMs

Kai Zhuang, Jiawei Zhang, Yumou Liu +10

Scientific Large Language Models (Sci-LLMs) have emerged as a promising frontier for accelerating biological discovery. However, these models face a fundamental challenge when proc…

q-bio.BM2025★ 3 cited

ODesign: A World Model for Biomolecular Interaction Design

Odin Zhang, Xujun Zhang, Haitao Lin +34

Biomolecular interactions underpin almost all biological processes, and their rational design is central to programming new biological functions. Generative AI models have emerged…

q-bio.BM2025

RiboPO: Preference Optimization for Structure- and Stability-Aware RNA Design

Minghao Sun, Hanqun Cao, Zhou Zhang +10

Designing RNA sequences that reliably adopt specified three-dimensional structures while maintaining thermodynamic stability remains challenging for synthetic biology and therapeut…

cs.CV2024

Deep Learning-Based Quasi-Conformal Surface Registration for Partial 3D Faces Applied to Facial Recognition

Yuchen Guo, Hanqun Cao, Lok Ming Lui

3D face registration is an important process in which a 3D face model is aligned and mapped to a template face. However, the task of 3D face registration becomes particularly chall…

q-bio.BM2022

Deciphering RNA Secondary Structure Prediction: A Probabilistic K-Rook Matching Perspective

Cheng Tan, Zhangyang Gao, Hanqun Cao +6

The secondary structure of ribonucleic acid (RNA) is more stable and accessible in the cell than its tertiary structure, making it essential for functional prediction. Although dee…

cs.AI2022★ 67 cited

A Survey on Generative Diffusion Model

Hanqun Cao, Cheng Tan, Zhangyang Gao +4

Deep generative models have unlocked another profound realm of human creativity. By capturing and generalizing patterns within data, we have entered the epoch of all-encompassing A…