amurugan  uchicago.edu
(773) 834 3146
Murugan lab
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Learning without neurons

My group is broadly interested in ’hardware’ implementations (e.g., in biomolecules, reaction networks, self-assembly, soft materials) of behaviors usually seen in ’software’ (e.g., learning, inference, error correction). In particular,  we work on how collective dynamics in physical and biological systems can generalize past experiences, i.e., learn, and respond differently to future inputs. 

These themes often require combining work in quantitative biology, non-equilibrium dynamics, and theoretical computer science.  Current work includes:

1.  Biological adaptation and evolution in changing environments
     (in circadian clocks with the Rust lab, in molecular evolution with
      the Wang and Ranganathan labs)

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



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)

Learning without neurons in physical systems 
N. Stern, A. Murugan
Annual Reviews of Condensed Matter Physics (to appear)

Standardized excitable elements for scalable engineering of far-from-equilibrium chemical networks
S W. Schaffter, K-L Chen, J O’Brien, M Noble, A Murugan, R Schulman
Nature Chemistry (to appear)

Ligand-receptor promiscuity enables cellular addressing
C Su, A Murugan, J Linton, A Yeluri, J Bois, H Klumpe, Y Antebi, M Elowitz
Cell Systems 2021

Learning to control active matter
M. Falk, V. Alizadehyazdi, H. Jaeger, A. Murugan
Physical Review Research 2021, arxiv

Roadmap on biology in time varying environments
A. Murugan et al
Physical Biology 2021

Proofreading through spatial gradients
Vahe Galstyan, Kabir Husain, Fangzhou Xiao, Arvind Murugan+, Rob Phillips+
eLife 2020; 9:e60415

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

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

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

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)