Research in the Dinner group centers on the statistical mechanics of systems far from equilibrium, particularly its application to understanding what is life.
Biological molecules often switch between conformations to function. Understanding these dynamics is important for understanding how the complex behaviors that we associate with living systems emerge from physical laws and for controlling these behaviors (e.g., for therapies). Simulations can reveal molecular dynamics in atomic detail, but identifying the key events can be challenging because typical simulations involve hundreds of thousands to millions of variables, and the sequence of events can vary from one run to another. While machine learning has revolutionized identifying patterns in high-dimensional data, a separation in time scales between the time steps in simulations (femtoseconds, set by the fastest motions) and biological processes (microseconds to hours) limits the data and, in turn, the ability of traditional machine-learning approaches to tackle this problem. My group is developing machine-learning approaches that leverage physics to learn molecular mechanisms with statistical confidence from relatively small amounts of simulation data. We are building on this expertise (i) to learn physical mechanisms from biological imaging and time-series data and (ii) to treat problems with separations in time scales in other disciplines.
Harvard University
A.B.
1994
Harvard University
Ph.D.
1999
University of Oxford
2001
University of California, Berkeley
Burroughs Welcome Fund Hitchings-Elion Postdoctoral Fellow
2003
The University of Chicago
Professor
Present
James Franck Institute
Director
2018
Physical Sciences Division, The University of Chicago
Deputy Dean
Present
Kwanghoon Jeong, Spencer C. Guo, Sammy Allaw, Aaron R. Dinner
bioRxiv 2024.10.08.617297; doi: https://doi.org/10.1101/2024.10.08.617297
Pengmei, Zihan, et al. “Geom2vec: Pretrained GNNs as Geometric Featurizers for Conformational Dynamics.” ArXiv.org, 2024, arxiv.org/abs/2409.19838.
Floyd, C., Dinner, A. R., Murugan, A., & Vaikuntanathan, S. (2024, September 9). Limits on the computational expressivity of non-equilibrium biophysical processes. arXiv.org. https://arxiv.org/abs/2409.05827
Chi, C., Weare, J., & Dinner, A. R. (2024, August 28). Sampling parameters of ordinary differential equations with Langevin dynamics that satisfy constraints. arXiv.org. https://arxiv.org/abs/2408.15505
Strahan, J., Lorpaiboon, C., Weare, J., & Dinner, A. R. (2024). BAD-NEUS: Rapidly converging trajectory stratification. The Journal of Chemical Physics, 161(8). https://doi.org/10.1063/5.0215975
Lorpaiboon, C., Guo, S. C., Strahan, J., Weare, J., & Dinner, A. R. (2024). Accurate estimates of dynamical statistics using memory. The Journal of Chemical Physics, 160(8). https://doi.org/10.1063/5.0187145
Qiu, Y., White, E. D., Munro, E. M., Vaikuntanathan, S., & Dinner, A. R. (2023, October 16). Elucidating the Role of Filament Turnover in Cortical Flow using Simulations and Representation Learning. arXiv.org. https://arxiv.org/abs/2310.10819
Strahan, John, et al. “Predicting Rare Events Using Neural Networks and Short-Trajectory Data.” Journal of Computational Physics, vol. 488, Sept. 2023, p. 112152, arxiv.org/pdf/2208.01717.pdf, doi:https://doi.org/10.1063/5.0151309
Strahan, John, et al. "Inexact Iterative Numerical Linear Algebra for Neural Network-Based Spectral Estimation and Rare-Event Prediction." J. Chem. Phys. , 6 July 2023. doi:https://doi.org/10.1063/5.0151309
Strahan, J., Guo, S. C., Lorpaiboon, C., Dinner, A. R., & Weare, J. (2023). Inexact iterative numerical linear algebra for neural network-based spectral estimation and rare-event prediction. The Journal of Chemical Physics, 159(1). https://doi.org/10.1063/5.0151309
Guo, S.C., Shen, R., Roux, B. et al. Dynamics of activation in the voltage-sensing domain of Ciona intestinalis phosphatase Ci-VSP. Nat Commun 15, 1408 (2024). https://doi.org/10.1038/s41467-024-45514-6
Arthur L. Kelly Faculty Prize for Exceptional Service in the Physical Sciences Division
2021
American Physical Society Fellowship
2016
American Chemical Society Hewlett-Packard Outstanding Junior Faculty Award
2009
Alfred P. Sloan Fellow
2008
NSF Career Award
2006
Searle Scholar
2005
Dreyfus New Faculty Award
2003
Linacre College EPA Cephalosporin Junior Research Fellow
2000 - 2001
Burroughs Wellcome Fund Hitchings-Elion Postdoctoral Fellow
1999
Voltage-sensing Protein Moves in Unexpected Ways in Anton Simulations