The Dinner group seeks to develop a theoretical understanding of how complex biological behavior arises from molecular interactions. Because the defining properties of living systems (growth, movement, and directed response to environmental stimuli) rely on irreversible energy consumption and dissipation, much of our research centers on stochastic processes far from equilibrium. We quantitatively analyze experimental data on living systems, construct physical models to interpret the observed statistics, and implement algorithms for efficiently simulating the dynamics of such models.

Research interests

Accelerating molecular simulations

sampling

We are developing, mathematically characterizing, and employing algorithms for enhancing the sampling of rare events and recovering their statistics.

Modeling living systems

sampling

We are building models to interpret dynamics observed in cells and exploring the behavior of these models both analytically and numerically.

Analyzing biological data

bioinformatics

We are developing and applying approaches for bioinformatics and image analysis in close collaboration with experimentalists.

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People

Present members of the group are listed below. Information about former members can be found here.
Aaron Dinner

Aaron Dinner

I am a Professor of Chemistry and the Director of the James Franck Institute at the University of Chicago. I also hold appointments in the Institute for Biophysical Dynamics, the Computation Institute, and the Institute for Genomics and Systems Biology. My group’s most well known contributions are to machine learning methods for interpreting complex biomolecular simulations, sampling methods for systems far from equilibrium, and models of hematopoietic cell fate choice. Much of my current work is collaborative, and many of my students and postdoctoral scholars are jointly mentored by experimentalists and/or statisticians. My honors include a Searle Scholarship, NSF CAREER Award, Sloan Fellowship, and participation in the 2010 and 2014 Latke-Hamantash Debates.

Prior to joining the faculty at Chicago, I obtained my undergraduate (AB in Biochemical Sciences, 1994) and graduate (PhD in Biophysics, 1999) degrees at Harvard University, where I worked with Martin Karplus on Monte Carlo methods and their application to protein folding. Subsequently, I pursued postdoctoral studies at the University of Oxford (1999-2001), where I used hybrid quantum-mechanical/molecular-mechanical (QM/MM) methods to elucidate mechanisms of DNA repair, and the University of California, Berkeley (2001-2003), where I worked with David Chandler on transition path sampling and Arup Chakraborty on models of T lymphocyte signaling.

website

professor | since 2003
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photo: Shiladitya Banerjee

Shiladitya Banerjee

My research involves developing physical models for living systems and materials over a broad range of scales, including biomolecules, macromolecular assemblies, living cells, tissues and organisms. I apply theoretical and computational methods from soft matter physics and statistical mechanics to understand how cellular assemblies organize their behavior for diverse physiological tasks.

website

postdoctoral scholar | since 2013
photo: Glen Hocky

Glen Hocky

My research interests broadly involve the applications of techniques from statistical mechanics and molecular modeling to better understand the mechanisms behind biological processes, particularly those involving interactions between macromolecules. Currently I am studying many aspects of the complex interactions occurring in the cell cytoskeleton.

website

postdoctoral scholar | since 2014
photo: Zhiyue Lu

Zhiyue Lu

I am interested in non-equilibrium statistical physics. I develop numerical methods to efficiently sample rare events. Another aspect of my research is designing models that help us better understand chemical reactions, information processing, biological processes and many other interesting phenomena far from thermal equilibrium.

website

postdoctoral scholar | since 2016
photo: Charles Mathews

Charles Mathews

I develop advanced algorithms for Bayesian Markov Chain Monte Carlo. I also work on using tools from molecular modeling to simulate catastrophic failure in the power grid.

postdoctoral scholar | since 2014
photo: Brian van Koten

Brian van Koten

My research focuses on building a deep understanding of enhanced sampling algorithms using numerical analysis.

postdoctoral scholar | since 2011
Simon Freedman

Simon Freedman

In my research, I use agent-based modeling to study emergent phenomena in actomyosin networks.

graduate student | since 2014
Herman Gudjonson

Herman Gudjonson

I study the gene regulatory networks that govern cell fate commitment using genome-wide and single-cell measurements.

graduate student | since 2013
Alan Hutchison

Alan Hutchison

My research focuses on developing computational methods and models to understand circadian rhythms, especially in the context of sparsely sampled high-throughput genome-wide data.

graduate student | since 2012
Eugene Leypunskiy

Eugene Leypunskiy

I am interested in the role circadian clocks play in fluctuating light-dark conditions that have presumably provided selective pressure for the evolution of biological timekeeping. How precise is the adaptation of circadian clocks to 24-hr light-dark cycles? What is the range of light-dark frequencies in which biological clocks can correctly anticipate these environmental transitions? In what circumstances do circadian timekeepers enhance reproductive fitness -- and why?

graduate student | since 2013
Monika Scholz

Monika Scholz

I study how the nervous system of our model system C. elegans integrates environmental cues to regulate its appetite using a novel microfluidic setup. The regulation of food intake plays a major role in controlling energy availability in organisms. To understand this process on a more fundamental level, I use different tools from time-series analysis to infer underlying principles of appetite regulations.

graduate student | since 2013

Jeremy Tempkin

I am interested in developing algorithms for sampling rare events in molecular simulations. My research in the Dinner group focuses on applications of the nonequilibrium umbrella sampling method which is suitable for use in systems driven far from equilibrium and can be applied to compute a variety of dynamical quantities. I also am interested in building Python-based programming tools designed to facilitate rapid prototyping of enhanced sampling algorithms for HPC applications.

graduate student | since 2013
Erik Thiede

Erik Thiede

Traditional enhanced sampling schemes are often limited to systems dominated by one or two important degrees of freedom. However, for many systems, such as disordered proteins, this is not the case. My research focuses on developing umbrella sampling algorithms for systems governed by many degrees of freedom.

graduate student | since 2014

Vicky To

graduate student | since 2015
photo: Catherine Triandafillou

Catherine Triandafillou

I study self-assembly processes in cells, specifically, those that occur during times of stress. Using both this and experimental approaches I hope to explain and predict the regulatory consequences of aggregation.

graduate student | since 2014

Bodhi Vani

graduate student | since 2015
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Recent publications

Selected recent publications are highlighted below. For a full list, see PubMed or Google Scholar.

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Eigenvector method for umbrella sampling enables error analysis
Erik Thiede, Brian Van Koten, Jonathan Weare, and Aaron R Dinner
arXiv:1603.04505 (2016) Link

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Cycling State that Can Lead to Glassy Dynamics in Intracellular Transport
Monika Scholz, Stanislav Burov, Kimberly L Weirich, Björn J Scholz, SM Ali Tabei, Margaret L Gardel, and Aaron R Dinner
Physical Review X 6, 011037 (2016) Link

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Improved statistical methods enable greater sensitivity in rhythm detection for genome-wide data
Alan L Hutchison, Mark Maienschein-Cline, Andrew H Chiang, SM Ali Tabei, Herman Gudjonson, Neil Bahroos, Ravi Allada, and Aaron R Dinner
PLoS Computational Biology 11, e1004094 (2015) Link

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Scaling laws governing stochastic growth and division of single bacterial cells
Srividya Iyer-Biswas, Charles S Wright, Jonathan T Henry, Klevin Lo, Stanislav Burov, Yihan Lin, Gavin E Crooks, Sean Crosson, Aaron R Dinner, and Norbert F Scherer
Proceedings of the National Academy of Sciences 111, 15912-15917 (2014) Link

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