Uploaded June 2025 | Updated September 2026, 2 weeks ago
Models, Inference and Algorithms
March 11, 2025
Broad Institute of MIT and Harvard
Primer: Heterogeneous reconstruction in cryo-EM
Rishwanth Raghu
Princeton University Department of Computer Science
Meeting: Machine learning for visualizing structural landscapes inside the cell
Ellen Zhong
Princeton University
Structural biology has been transformed by breakthroughs in deep learning methods for protein structure prediction. In parallel, advances in cryo-electron microscopy and tomography have produced new opportunities to study the dynamics and interactions of biomolecular complexes. In this seminar, I will describe the algorithmic challenges at the frontier of structure determination via cryo-EM. I will overview cryoDRGN, a machine learning system for heterogeneous cryo-EM and cryo-ET reconstruction. Along the way, I will overview recent progress in our group on reconstructing complex mixtures, developing a challenging benchmark for structural heterogeneity, and visualizing dynamic biomolecular complexes in situ.
Bio: Ellen Zhong is an Assistant Professor of Computer Science at Princeton University where she is also affiliated with the Princeton Laboratory for Artificial Intelligence, the Center for Statistics and Machine Learning, and the Omenn-Darling Bioengineering Institute. Her group’s research spans methodological research in AI and computer vision, as well as close collaboration with experimentalists in molecular and structural biology. Previously, she has worked on the AlphaFold team at Google DeepMind and at D. E. Shaw Research on molecular dynamics for drug discovery. She obtained her B.S. from the University of Virginia in 2014 and her Ph.D. from MIT in 2022 before joining the Princeton faculty.
For more information visit: broadinstitute.org/talks/spring-2025/mia
Copyright Broad Institute, 2024. All rights reserved.
Models, Inference and Algorithms
March 11, 2025
Broad Institute of MIT and Harvard
Primer: Heterogeneous reconstruction in cryo-EM
Rishwanth Raghu
Princeton University Department of Computer Science
Meeting: Machine learning for visualizing structural landscapes inside the cell
Ellen Zhong
Princeton University
Structural biology has been transformed by breakthroughs in deep learning methods for protein structure prediction. In parallel, advances in cryo-electron microscopy and tomography have produced new opportunities to study the dynamics and interactions of biomolecular complexes. In this seminar, I will describe the algorithmic challenges at the frontier of structure determination via cryo-EM. I will overview cryoDRGN, a machine learning system for heterogeneous cryo-EM and cryo-ET reconstruction. Along the way, I will overview recent progress in our group on reconstructing complex mixtures, developing a challenging benchmark for structural heterogeneity, and visualizing dynamic biomolecular complexes in situ.
Bio: Ellen Zhong is an Assistant Professor of Computer Science at Princeton University where she is also affiliated with the Princeton Laboratory for Artificial Intelligence, the Center for Statistics and Machine Learning, and the Omenn-Darling Bioengineering Institute. Her group’s research spans methodological research in AI and computer vision, as well as close collaboration with experimentalists in molecular and structural biology. Previously, she has worked on the AlphaFold team at Google DeepMind and at D. E. Shaw Research on molecular dynamics for drug discovery. She obtained her B.S. from the University of Virginia in 2014 and her Ph.D. from MIT in 2022 before joining the Princeton faculty.
For more information visit: broadinstitute.org/talks/spring-2025/mia
Copyright Broad Institute, 2024. All rights reserved.
