Ellen D. Zhong

This paper introduces an AI system for automated small molecule structure elucidation from NMR spectra, combining generative models with reasoning agents to outperform existing tools.

The paper introduces the CAHRA Challenge, a community-wide assessment of cryo-EM heterogeneous reconstruction algorithms using three benchmark datasets.

This paper introduces T-REX, an agentic framework for protein binder design that adaptively allocates compute resources across methods, achieving higher throughput of structurally distinct hits than baselines.

The paper presents a cryo-EM conformational heterogeneity challenge to evaluate and improve methods for analyzing molecular motions in heterogeneous samples.

The paper introduces cryoDRGN-AI, a method for ab initio 3D reconstruction of cryo-EM and cryo-ET datasets, revealing new conformational states and unresolved motions.

The paper uses cryo-electron tomography to reveal the in situ architecture of the polar tube invasion apparatus in microsporidian parasites.

This paper identifies two conformations of the γ-tubulin ring complex (γ-TuRC) using cryo-EM and proposes a model for how conformational changes facilitate microtubule nucleation.

CryoDRGN uses deep neural networks to reconstruct heterogeneous protein complexes and their motion from cryo-EM data, revealing previously unseen structural states.

The paper uses neural language models to predict viral escape mutations by modeling semantic change and grammaticality in viral sequences.

This paper introduces RNA timestamps to infer RNA age using A-to-I editing, enabling temporal analysis of gene expression in single-cell RNA sequencing.