amurugan  uchicago.edu
(773) 834 3146
Murugan lab
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Research interests

We work on problems in quantitative biology, non-equilibrium dynamics, and theoretical computer science.   A frequent question is how collective dynamics in physical and biological systems can generalize past experiences, i.e., learn, and respond differently to future inputs. 

Current work includes:
1.  Biological learning and adaptation in changing environments
     (in circadian clocks with the Rust lab, in molecular evolution with
      the Wang and Ranganathan labs, in neural networks)

2. Learned behaviors in materials
     (elastic materials, molecular systems with the Winfree lab, active materials).



Openings: If you are interested in working on such themes as a postdoc, graduate student or undergrad, contact  amurugan@uchicago.edu. 

Funding: Our work is primarily supported by the NSF and a Simons Foundation Investigator award. Lab members have been supported by the James S. McDonnell Foundation and NSF fellowships.
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Some recent publications            (List + summaries here)

Continual learning of multiple memories in mechanical networks 
M. Stern, M. Pinson, A. Murugan
Physical Review X (Aug 2020)   (arxiv version)

Proofreading through spatial gradients
Vahe Galstyan, Kabir Husain, Fangzhou Xiao, Arvind Murugan+, Rob Phillips+
bioRxiv 2020


Supervised learning through physical changes in a mechanical system
M. Stern, C. Arinze, L. Perez, S. Palmer, A. Murugan
PNAS (in press, 2020) 

Physical constraints on epistasis
K. Husain, A. Murugan
Molecular Biology and Evolution (MBE) (in press, 2020) ,  arxiv

Tuning environmental timescales to evolve and maintain generalists
V. Sachdeva*, K. Husain*, J. Sheng, S. Wang+, A. Murugan+
PNAS (April 2020) 

Non-equilibrium statistical mechanics of continuous attractors
W. Zhong, Z. Lu, D.J.Schwab+, A. Murugan+
Neural Computation (2020)  pdf

Kalman-like Self-Tuned Sensitivity in Biophysical Sensing 
K Husain, W Pittayakanchit, G Pattanayak, M J Rust, A. Murugan
Cell Systems 2019, 459–465.e6

Temporal pattern recognition through analog molecular computation
 J O'Brien, A. Murugan
ACS Synthetic Biology (March 2019)
Popular summary by MIT Tech Review


Bioinspired nonequilibrium search for novel materials
A. Murugan, H. Jaeger 
MRS Bulletin 44(2):96-105       pdf here

Information content of downwelling skylight for non-imaging visual systems
 with: R. Thiermann, A. Sweeney
bioRxiv (Sep 2018) 
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Shaping the topology of folding pathways in mechanical systems
with: M. Stern, V. Jayaram,
Nature Communications 9:4303 (2018)

​Biophysical clocks face a trade-off between internal and external noise resistance
 with: W. Pittayakanchit*, Z. Lu*, J. Chew, M. Rust
eLife 2018;7:e37624

High Protein Copy Number Is Required to Suppress Stochasticity in the Cyanobacterial Circadian Clock 
 with: J. Chew, E. Leypunskiy, J. Lin, M. Rust
Nature Communications 9:3004 (2018)

Shaping dynamical pathways in mechanical systems
with: M. Stern, V. Jayaram
Nature Communications 9:4303 (2018)

 The difficulty of folding self-folding origami
 with: M. Stern, M. Pinson
Physical Review X,  arXiv link (2017) 

Self-folding origami at any energy scale
 with: M. Pinson*, M. Stern*, A Ferrero, T.Witten, E. Chen
Nature Communications 8:15477 (2017) 

 Associative pattern recognition through macro-molecular self-assembly
 with: W. Zhong, D.J. Schwab
Journal of Statistical Physics,  Volume 167, Issue 3–4, May 2017

Topologically protected modes in non-equilibrium stochastic systems
with: S. Vaikuntanathan
Nature Communications (Jan 2017) 

The Information Capacity of Specific Interactions
 with: M. Huntley, M. Brenner
Proceedings of the National Academy of Sciences (May 2016)

Receptor arrays optimized for natural odor statistics,
with: D. Zwicker, M. Brenner
Proceedings of the National Academy of Sciences (Apr 2016)

Biological implications of dynamical phases in non-equilibrium reaction networks,
with: S. Vaikuntanathan
invited contribution, Journal of Statistical Physics (2016, 162 (5))
 
Undesired usage and the robust self-assembly of heterogeneous structures,   
with: J. Zou, and M. Brenner 
Nature Communications 6, 6203 (Jan 2015) 

Multifarious Assembly Mixtures: Systems Allowing Retrieval of Diverse Stored Structures,           
with: Z. Zeravcic, S. Leibler and M. Brenner 
Proceedings of the National Academy of Sciences 112(1) 54-59 (Dec 2014)