|
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 learning and adaptation 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. |
|
Some recent publications (List + summaries here) |
|
Ligand-receptor promiscuity enables cellular addressing
C Su, A Murugan, J Linton, A Yeluri, J Bois, H Klumpe, Y Antebi, M Elowitz bioarxiv Learning to control active matter M. Falk, V. Alizadehyazdi, H. Jaeger, A. Murugan Physical Review Research (to appear), 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) 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) |