Literature DB >> 19381543

Network dynamics.

Herbert M Sauro1.   

Abstract

Probably one of the most characteristic features of a living system is its continual propensity to change as it juggles the demands of survival with the need to replicate. Internally these adjustments are manifest as changes in metabolite, protein, and gene activities. Such changes have become increasingly obvious to experimentalists, with the advent of high-throughput technologies. In this chapter we highlight some of the quantitative approaches used to rationalize the study of cellular dynamics. The chapter focuses attention on the analysis of quantitative models based on differential equations using biochemical control theory. Basic pathway motifs are discussed, including straight chain, branched, and cyclic systems. In addition, some of the properties conferred by positive and negative feedback loops are discussed, particularly in relation to bistability and oscillatory dynamics.

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Year:  2009        PMID: 19381543      PMCID: PMC2793415          DOI: 10.1007/978-1-59745-243-4_13

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  53 in total

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Authors:  Nick I Markevich; Jan B Hoek; Boris N Kholodenko
Journal:  J Cell Biol       Date:  2004-01-26       Impact factor: 10.539

9.  Oscillations and variability in the p53 system.

Authors:  Naama Geva-Zatorsky; Nitzan Rosenfeld; Shalev Itzkovitz; Ron Milo; Alex Sigal; Erez Dekel; Talia Yarnitzky; Yuvalal Liron; Paz Polak; Galit Lahav; Uri Alon
Journal:  Mol Syst Biol       Date:  2006-06-13       Impact factor: 11.429

10.  Topology and robustness in the Drosophila segment polarity network.

Authors:  Nicholas T Ingolia
Journal:  PLoS Biol       Date:  2004-06-15       Impact factor: 8.029

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  4 in total

1.  Robust L-type calcium current expression following heterozygous knockout of the Cav1.2 gene in adult mouse heart.

Authors:  Barbara Rosati; Qinghong Yan; Mi Sun Lee; Shian-Ren Liou; Brian Ingalls; Jason Foell; Timothy J Kamp; David McKinnon
Journal:  J Physiol       Date:  2011-04-26       Impact factor: 5.182

2.  The in silico macrophage: toward a better understanding of inflammatory disease.

Authors:  Peter Ghazal; Steven Watterson; Kevin Robertson; David C Kluth
Journal:  Genome Med       Date:  2011-01-22       Impact factor: 11.117

Review 3.  Phenotypic Heterogeneity in Tumor Progression, and Its Possible Role in the Onset of Cancer.

Authors:  Saniya Deshmukh; Supreet Saini
Journal:  Front Genet       Date:  2020-11-30       Impact factor: 4.599

Review 4.  Ultrasensitive response motifs: basic amplifiers in molecular signalling networks.

Authors:  Qiang Zhang; Sudin Bhattacharya; Melvin E Andersen
Journal:  Open Biol       Date:  2013-04-24       Impact factor: 6.411

  4 in total

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