Generalized Glauber Dynamics for Inference in Biology
Large interacting systems in biology often exhibit emergent dynamics, such as coexistence of multiple timescales, manifested by fat tails in the distribution of waiting times. While existing tools in statistical inference, such as maximum entropy models, reproduce the empirical steady-state distribu...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Physical Society
2023-12-01
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| Series: | Physical Review X |
| Online Access: | http://doi.org/10.1103/PhysRevX.13.041053 |
| _version_ | 1797385817903071232 |
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| author | Xiaowen Chen Maciej Winiarski Alicja Puścian Ewelina Knapska Aleksandra M. Walczak Thierry Mora |
| author_facet | Xiaowen Chen Maciej Winiarski Alicja Puścian Ewelina Knapska Aleksandra M. Walczak Thierry Mora |
| author_sort | Xiaowen Chen |
| collection | DOAJ |
| description | Large interacting systems in biology often exhibit emergent dynamics, such as coexistence of multiple timescales, manifested by fat tails in the distribution of waiting times. While existing tools in statistical inference, such as maximum entropy models, reproduce the empirical steady-state distributions, it remains challenging to learn dynamical models. We present a novel inference method, called generalized Glauber dynamics. Constructed through a non-Markovian fluctuation dissipation theorem, generalized Glauber dynamics tunes the dynamics of an interacting system, while keeping the steady-state distribution fixed. We motivate the need for the method on real data from Eco-HAB, an automated habitat for testing behavior in groups of mice under seminaturalistic conditions, and present it on simple Ising spin systems. We show its applicability for experimental data by inferring dynamical models of social interactions in a group of mice that reproduce both its collective behavior and the long tails observed in individual dynamics. |
| first_indexed | 2024-03-08T21:59:50Z |
| format | Article |
| id | doaj.art-1f103ac0e0704ab9bfefbcb752226ebb |
| institution | Directory Open Access Journal |
| issn | 2160-3308 |
| language | English |
| last_indexed | 2024-03-08T21:59:50Z |
| publishDate | 2023-12-01 |
| publisher | American Physical Society |
| record_format | Article |
| series | Physical Review X |
| spelling | doaj.art-1f103ac0e0704ab9bfefbcb752226ebb2023-12-19T15:29:12ZengAmerican Physical SocietyPhysical Review X2160-33082023-12-0113404105310.1103/PhysRevX.13.041053Generalized Glauber Dynamics for Inference in BiologyXiaowen ChenMaciej WiniarskiAlicja PuścianEwelina KnapskaAleksandra M. WalczakThierry MoraLarge interacting systems in biology often exhibit emergent dynamics, such as coexistence of multiple timescales, manifested by fat tails in the distribution of waiting times. While existing tools in statistical inference, such as maximum entropy models, reproduce the empirical steady-state distributions, it remains challenging to learn dynamical models. We present a novel inference method, called generalized Glauber dynamics. Constructed through a non-Markovian fluctuation dissipation theorem, generalized Glauber dynamics tunes the dynamics of an interacting system, while keeping the steady-state distribution fixed. We motivate the need for the method on real data from Eco-HAB, an automated habitat for testing behavior in groups of mice under seminaturalistic conditions, and present it on simple Ising spin systems. We show its applicability for experimental data by inferring dynamical models of social interactions in a group of mice that reproduce both its collective behavior and the long tails observed in individual dynamics.http://doi.org/10.1103/PhysRevX.13.041053 |
| spellingShingle | Xiaowen Chen Maciej Winiarski Alicja Puścian Ewelina Knapska Aleksandra M. Walczak Thierry Mora Generalized Glauber Dynamics for Inference in Biology Physical Review X |
| title | Generalized Glauber Dynamics for Inference in Biology |
| title_full | Generalized Glauber Dynamics for Inference in Biology |
| title_fullStr | Generalized Glauber Dynamics for Inference in Biology |
| title_full_unstemmed | Generalized Glauber Dynamics for Inference in Biology |
| title_short | Generalized Glauber Dynamics for Inference in Biology |
| title_sort | generalized glauber dynamics for inference in biology |
| url | http://doi.org/10.1103/PhysRevX.13.041053 |
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