Parity and time reversal elucidate both decision-making in empirical models and attractor scaling in critical Boolean networks-Reference-Cited by-同舟云学术

Parity and time reversal elucidate both decision-making in empirical models and attractor scaling in critical Boolean networks

Published:2021-07-16 Issue:29 Volume:7 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Rozum Jordan C.¹^ORCID,Gómez Tejeda Zañudo Jorge²³^ORCID,Gan Xiao⁴⁵,Deritei Dávid⁶,Albert Réka¹⁷^ORCID

Affiliation:

1. Department of Physics, The Pennsylvania State University, University Park, PA 16802, USA.

2. Eli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.

3. Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA.

4. Network Science Institute and Department of Physics, Northeastern University, Boston, MA 02115, USA.

5. Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA.

6. Department of Molecular Biology, Semmelweis University, Budapest, Hungary.

7. Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA.

Abstract

Fast analysis of attractor commitment in networks of stochastic switches answers a 50-year-old attractor scaling question.

Funder

National Science Foundation

Stand Up To Cancer

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference100 articles.

1. N. Boccara Modeling Complex Systems (Springer Science & Business Media 2010).

2. F. Schweitzer Brownian Agents and Active Particles: Collective Dynamics in the Natural and Social Sciences (Springer Science & Business Media 2007).

3. C. R. Shalizi Methods and techniques of complex systems science: An overview in Topics in Biomedical Engineering International Book Series (Springer 2006) pp. 33–114.

4. H. Sayama Introduction to the Modeling and Analysis of Complex Systems (Open SUNY Textbooks 2015).

5. Modelling dynamical processes in complex socio-technical systems

Cited by 34 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MIFuGP: Boolean network inference from multivariate time series using fuzzy genetic programming;Information Sciences;2024-10

2. Irreversibility in bacterial regulatory networks;Science Advances;2024-08-30

3. A network-based modeling framework reveals the core signal transduction network underlying high carbon dioxide-induced stomatal closure in guard cells;PLOS Biology;2024-05-01

4. Discrete-state models identify pathway specific B cell states across diseases and infections at single-cell resolution;Journal of Theoretical Biology;2024-04

5. Boolean Networks as Predictive Models of Emergent Biological Behaviors;2024-03-04