Treffer: A meta-analysis of Boolean network models reveals design principles of gene regulatory networks.
Title:
A meta-analysis of Boolean network models reveals design principles of gene regulatory networks.
Authors:
Kadelka C; Department of Mathematics, Iowa State University, Ames, IA 50011, USA., Butrie TM; Department of Aerospace Engineering, Iowa State University, Ames, IA 50011, USA., Hilton E; Department of Computer Science, Iowa State University, Ames, IA 50011, USA.; Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011, USA., Kinseth J; Department of Mathematics, Iowa State University, Ames, IA 50011, USA., Schmidt A; Department of Computer Science, Iowa State University, Ames, IA 50011, USA., Serdarevic H; Department of Mathematics, Iowa State University, Ames, IA 50011, USA.
Source:
Science advances [Sci Adv] 2024 Jan 12; Vol. 10 (2), pp. eadj0822. Date of Electronic Publication: 2024 Jan 12.
Publication Type:
Meta-Analysis; Journal Article; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: American Association for the Advancement of Science Country of Publication: United States NLM ID: 101653440 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2375-2548 (Electronic) Linking ISSN: 23752548 NLM ISO Abbreviation: Sci Adv Subsets: MEDLINE
Imprint Name(s):
Original Publication: Washington, DC : American Association for the Advancement of Science, [2015]-
MeSH Terms:
References:
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BMC Syst Biol. 2012 Aug 07;6:96. (PMID: 22871178)
Nat Genet. 2002 May;31(1):64-8. (PMID: 11967538)
Mol Syst Biol. 2010 Nov 2;6:425. (PMID: 21045819)
Science. 2002 Aug 16;297(5584):1183-6. (PMID: 12183631)
BMC Syst Biol. 2014 Jun 25;8:75. (PMID: 24970389)
Comput Struct Biotechnol J. 2020 Mar 10;18:571-582. (PMID: 32257043)
J Theor Biol. 1974 Mar;44(1):167-90. (PMID: 4595774)
WIREs Mech Dis. 2022 Mar;14(2):e1544. (PMID: 35266649)
Mol Syst Biol. 2008;4:203. (PMID: 18628744)
Proc Natl Acad Sci U S A. 2021 Mar 23;118(12):. (PMID: 33737396)
Mol Biosyst. 2011 Dec;7(12):3253-70. (PMID: 21968890)
Nature. 2003 Jan 2;421(6918):63-6. (PMID: 12511954)
J Theor Biol. 2002 Oct 7;218(3):331-41. (PMID: 12381434)
PLoS One. 2008 Jun 18;3(6):e2456. (PMID: 18560561)
Nature. 2004 Sep 16;431(7006):308-12. (PMID: 15372033)
Nat Rev Genet. 2005 Jun;6(6):451-64. (PMID: 15883588)
J Mol Biol. 2003 Nov 21;334(2):197-204. (PMID: 14607112)
Bull Math Biol. 2012 Feb;74(2):422-33. (PMID: 22139748)
Phys Rev Lett. 2018 Sep 28;121(13):138102. (PMID: 30312104)
PLoS One. 2013 Jul 23;8(7):e69132. (PMID: 23935937)
J R Soc Interface. 2022 Jan;19(186):20210659. (PMID: 35042384)
PLoS One. 2013 Apr 18;8(4):e61757. (PMID: 23637902)
Nature. 2012 Sep 6;489(7414):91-100. (PMID: 22955619)
Phys Rev Lett. 2004 Jul 23;93(4):048701. (PMID: 15323803)
Proc Natl Acad Sci U S A. 2003 Oct 14;100(21):11980-5. (PMID: 14530388)
Bull Math Biol. 1995 Mar;57(2):247-76. (PMID: 7703920)
Entropy (Basel). 2023 Feb 18;25(2):. (PMID: 36832740)
Nucleic Acids Res. 2003 Jan 1;31(1):374-8. (PMID: 12520026)
Cell. 2004 Sep 17;118(6):675-85. (PMID: 15369668)
Semin Cell Dev Biol. 2019 Apr;88:67-79. (PMID: 29782925)
Science. 1999 Oct 15;286(5439):509-12. (PMID: 10521342)
PRX Life. 2023 Dec;1(2):. (PMID: 38487681)
Mol Biosyst. 2013 Sep;9(9):2248-58. (PMID: 23868318)
Sci Adv. 2018 Mar 28;4(3):eaap9751. (PMID: 29670941)
J Theor Biol. 2007 Apr 7;245(3):433-48. (PMID: 17188715)
Nucleic Acids Res. 2018 Jan 4;46(D1):D260-D266. (PMID: 29140473)
Nucleic Acids Res. 2016 Jan 4;44(D1):D133-43. (PMID: 26527724)
PLoS Comput Biol. 2012 Jan;8(1):e1002345. (PMID: 22253585)
Cell. 1999 Jul 9;98(1):1-4. (PMID: 10412974)
Nature. 1997 Jul 10;388(6638):167-71. (PMID: 9217155)
Trends Plant Sci. 2017 Jan;22(1):66-80. (PMID: 27814969)
Proc Natl Acad Sci U S A. 2003 Dec 9;100(25):14796-9. (PMID: 14657375)
Bioessays. 2000 Apr;22(4):372-80. (PMID: 10723034)
J Theor Biol. 1969 Mar;22(3):437-67. (PMID: 5803332)
Nat Rev Mol Cell Biol. 2008 Oct;9(10):770-80. (PMID: 18797474)
NPJ Syst Biol Appl. 2023 Apr 4;9(1):10. (PMID: 37015937)
Science. 2002 Oct 25;298(5594):824-7. (PMID: 12399590)
PNAS Nexus. 2022 Apr 15;1(1):pgac017. (PMID: 36712790)
Entry Date(s):
Date Created: 20240112 Date Completed: 20240115 Latest Revision: 20250613
Update Code:
20250614
PubMed Central ID:
PMC10786419
DOI:
10.1126/sciadv.adj0822
PMID:
38215198
Database:
MEDLINE
Weitere Informationen
Gene regulatory networks (GRNs) play a central role in cellular decision-making. Understanding their structure and how it impacts their dynamics constitutes thus a fundamental biological question. GRNs are frequently modeled as Boolean networks, which are intuitive, simple to describe, and can yield qualitative results even when data are sparse. We assembled the largest repository of expert-curated Boolean GRN models. A meta-analysis of this diverse set of models reveals several design principles. GRNs exhibit more canalization, redundancy, and stable dynamics than expected. Moreover, they are enriched for certain recurring network motifs. This raises the important question why evolution favors these design mechanisms.