Literature DB >> 22127955

Guiding the self-organization of random Boolean networks.

Carlos Gershenson1.   

Abstract

Random Boolean networks (RBNs) are models of genetic regulatory networks. It is useful to describe RBNs as self-organizing systems to study how changes in the nodes and connections affect the global network dynamics. This article reviews eight different methods for guiding the self-organization of RBNs. In particular, the article is focused on guiding RBNs toward the critical dynamical regime, which is near the phase transition between the ordered and dynamical phases. The properties and advantages of the critical regime for life, computation, adaptability, evolvability, and robustness are reviewed. The guidance methods of RBNs can be used for engineering systems with the features of the critical regime, as well as for studying how natural selection evolved living systems, which are also critical.

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Mesh:

Year:  2011        PMID: 22127955      PMCID: PMC3414703          DOI: 10.1007/s12064-011-0144-x

Source DB:  PubMed          Journal:  Theory Biosci        ISSN: 1431-7613            Impact factor:   1.919


  10 in total

Review 1.  Shape-dependent control of cell growth, differentiation, and apoptosis: switching between attractors in cell regulatory networks.

Authors:  S Huang; D E Ingber
Journal:  Exp Cell Res       Date:  2000-11-25       Impact factor: 3.905

2.  Genetic network models and statistical properties of gene expression data in knock-out experiments.

Authors:  R Serra; M Villani; A Semeria
Journal:  J Theor Biol       Date:  2004-03-07       Impact factor: 2.691

3.  Distributed robustness versus redundancy as causes of mutational robustness.

Authors:  Andreas Wagner
Journal:  Bioessays       Date:  2005-02       Impact factor: 4.345

4.  Principles of the self-organizing dynamic system.

Authors:  W R ASHBY
Journal:  J Gen Psychol       Date:  1947-10

5.  Guided self-organization.

Authors:  Mikhail Prokopenko
Journal:  HFSP J       Date:  2009-10-07

6.  Natural or internal selection? The case of canalization in complex evolutionary systems.

Authors:  Alexander Riegler
Journal:  Artif Life       Date:  2008       Impact factor: 0.667

7.  Degeneracy: a design principle for achieving robustness and evolvability.

Authors:  James Whitacre; Axel Bender
Journal:  J Theor Biol       Date:  2009-11-17       Impact factor: 2.691

8.  Collective dynamics of 'small-world' networks.

Authors:  D J Watts; S H Strogatz
Journal:  Nature       Date:  1998-06-04       Impact factor: 49.962

9.  PERSPECTIVE: COMPLEX ADAPTATIONS AND THE EVOLUTION OF EVOLVABILITY.

Authors:  Günter P Wagner; Lee Altenberg
Journal:  Evolution       Date:  1996-06       Impact factor: 3.694

10.  Metabolic stability and epigenesis in randomly constructed genetic nets.

Authors:  S A Kauffman
Journal:  J Theor Biol       Date:  1969-03       Impact factor: 2.691

  10 in total
  12 in total

1.  Guided self-organization: perception-action loops of embodied systems.

Authors:  Nihat Ay; Ralf Der; Mikhail Prokopenko
Journal:  Theory Biosci       Date:  2012-09       Impact factor: 1.919

Review 2.  Endogenous bioelectrical networks store non-genetic patterning information during development and regeneration.

Authors:  Michael Levin
Journal:  J Physiol       Date:  2014-06-01       Impact factor: 5.182

3.  The effective graph reveals redundancy, canalization, and control pathways in biochemical regulation and signaling.

Authors:  Alexander J Gates; Rion Brattig Correia; Xuan Wang; Luis M Rocha
Journal:  Proc Natl Acad Sci U S A       Date:  2021-03-23       Impact factor: 12.779

Review 4.  Structural determinants of criticality in biological networks.

Authors:  Sergi Valverde; Sebastian Ohse; Malgorzata Turalska; Bruce J West; Jordi Garcia-Ojalvo
Journal:  Front Physiol       Date:  2015-05-08       Impact factor: 4.566

5.  Molecular bioelectricity: how endogenous voltage potentials control cell behavior and instruct pattern regulation in vivo.

Authors:  Michael Levin
Journal:  Mol Biol Cell       Date:  2014-12-01       Impact factor: 4.138

6.  Limit cycle dynamics can guide the evolution of gene regulatory networks towards point attractors.

Authors:  Stuart P Wilson; Sebastian S James; Daniel J Whiteley; Leah A Krubitzer
Journal:  Sci Rep       Date:  2019-11-14       Impact factor: 4.379

7.  An Information-Theoretic Approach to Self-Organisation: Emergence of Complex Interdependencies in Coupled Dynamical Systems.

Authors:  Fernando Rosas; Pedro A M Mediano; Martín Ugarte; Henrik J Jensen
Journal:  Entropy (Basel)       Date:  2018-10-16       Impact factor: 2.524

8.  Guiding the Self-Organization of Cyber-Physical Systems.

Authors:  Carlos Gershenson
Journal:  Front Robot AI       Date:  2020-04-03

9.  Field-Control, Phase-Transitions, and Life's Emergence.

Authors:  Gargi Mitra-Delmotte; A N Mitra
Journal:  Front Physiol       Date:  2012-10-05       Impact factor: 4.566

10.  On Markov blankets and hierarchical self-organisation.

Authors:  Ensor Rafael Palacios; Adeel Razi; Thomas Parr; Michael Kirchhoff; Karl Friston
Journal:  J Theor Biol       Date:  2019-11-20       Impact factor: 2.691

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