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Hanqun Cao

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#machine learning Preprint Oct 2026

RNADyn: A Benchmark for Generating and Understanding RNA Dynamics

Ribonucleic acid (RNA) functions through conformational changes that are not fully captured by static structures. However, large-scale standardized RNA dynamics data remain limited, and existing approaches typically treat trajectory generation and dynamics understanding as separate objectives. Here, we introduce RNADyn...

Yi-Ming Huang, L. Bastian, Hanqun Cao et al. · 0 citations
Open access Aug 2026

Peptide structural plasticity is predictable from sequence and environment

ApexFold, an environment-conditioned AI framework that combines sequence representations with physicochemical descriptors of the surrounding medium to predict circular-dichroism-derived fractions of α-helical, β-like, and unstructured conformations is developed.

M. D. Torres, Hanqun Cao, César de la Fuente-Núñez · 0 citations

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