Literature DB >> 19638613

The complexity of cell signaling and the need for a new mechanics.

William S Hlavacek1, James R Faeder.   

Abstract

Cell signaling systems respond to multiple inputs, such as ligands of cell-surface receptors; and produce multiple outputs, such as changes in gene expression and cellular activities, including motility, proliferation, and death. This "macroscopic" input-output behavior is generated by a web of molecular interactions that can be viewed as taking place at a lower, "microscopic" level. These interactions prominently involve posttranslational modification of proteins and the nucleation of protein complexes. Behaviors at both the micro- and macroscopic levels are complex and must be probed systematically and characterized quantitatively as a prelude to the development of a predictive understanding of a cell signaling system. We must also have a theoretical framework or a mechanics within which we can determine how macroscopic behaviors emerge from known microscopic behaviors or change with manipulations of microscopic behaviors. To connect behaviors at both levels, we suggest that a new mechanics is now required. Newly available data support the idea that this mechanics should enable one to track the site-specific details of molecular interactions in a model, such as the phosphorylation status of individual amino acid residues within a protein.

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Year:  2009        PMID: 19638613     DOI: 10.1126/scisignal.281pe46

Source DB:  PubMed          Journal:  Sci Signal        ISSN: 1945-0877            Impact factor:   8.192


  13 in total

1.  Communications: Hamiltonian regulated cell signaling network.

Authors:  Ge Wang; Muhammad H Zaman
Journal:  J Chem Phys       Date:  2010-03-28       Impact factor: 3.488

Review 2.  Systems biology in immunology: a computational modeling perspective.

Authors:  Ronald N Germain; Martin Meier-Schellersheim; Aleksandra Nita-Lazar; Iain D C Fraser
Journal:  Annu Rev Immunol       Date:  2011       Impact factor: 28.527

3.  Rule-based modelling and simulation of biochemical systems with molecular finite automata.

Authors:  J Yang; X Meng; W S Hlavacek
Journal:  IET Syst Biol       Date:  2010-11       Impact factor: 1.615

Review 4.  Multiscale models of cell signaling.

Authors:  Sameer S Bajikar; Kevin A Janes
Journal:  Ann Biomed Eng       Date:  2012-04-03       Impact factor: 3.934

5.  A multiscale model of the regulation of aquaporin 2 recycling.

Authors:  Christoph Leberecht; Michael Schroeder; Dirk Labudde
Journal:  NPJ Syst Biol Appl       Date:  2022-05-09

6.  A general model for multilocus epistatic interactions in case-control studies.

Authors:  Zhong Wang; Tian Liu; Zhenwu Lin; John Hegarty; Walter A Koltun; Rongling Wu
Journal:  PLoS One       Date:  2010-08-18       Impact factor: 3.240

7.  RuleMonkey: software for stochastic simulation of rule-based models.

Authors:  Joshua Colvin; Michael I Monine; Ryan N Gutenkunst; William S Hlavacek; Daniel D Von Hoff; Richard G Posner
Journal:  BMC Bioinformatics       Date:  2010-07-30       Impact factor: 3.169

8.  Propagation of kinetic uncertainties through a canonical topology of the TLR4 signaling network in different regions of biochemical reaction space.

Authors:  Jayson Gutiérrez; Georges St Laurent; Silvio Urcuqui-Inchima
Journal:  Theor Biol Med Model       Date:  2010-03-15       Impact factor: 2.432

9.  Cuckoo search epistasis: a new method for exploring significant genetic interactions.

Authors:  M Aflakparast; H Salimi; A Gerami; M-P Dubé; S Visweswaran; A Masoudi-Nejad
Journal:  Heredity (Edinb)       Date:  2014-02-19       Impact factor: 3.821

10.  SRC Homology 2 Domain Binding Sites in Insulin, IGF-1 and FGF receptor mediated signaling networks reveal an extensive potential interactome.

Authors:  Bernard A Liu; Brett W Engelmann; Karl Jablonowski; Katherine Higginbotham; Andrew B Stergachis; Piers D Nash
Journal:  Cell Commun Signal       Date:  2012-09-14       Impact factor: 5.712

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