Literature DB >> 19454649

Deciphering signaling outcomes from a system of complex networks.

Robert C Hsueh1, Madhusudan Natarajan, Iain Fraser, Blake Pond, Jamie Liu, Susanne Mumby, Heping Han, Lily I Jiang, Melvin I Simon, Ronald Taussig, Paul C Sternweis.   

Abstract

Cellular signal transduction machinery integrates information from multiple inputs to actuate discrete cellular behaviors. Interaction complexity exists when an input modulates the output behavior that results from other inputs. To address whether this machinery is iteratively complex--that is, whether increasing numbers of inputs produce exponential increases in discrete cellular behaviors--we examined the modulated secretion of six cytokines from macrophages in response to up to five-way combinations of an agonist of Toll-like receptor 4, three cytokines, and conditions that activated the cyclic adenosine monophosphate pathway. Although all of the selected ligands showed synergy in paired combinations, few examples of nonadditive outputs were found in response to higher-order combinations. This suggests that most potential interactions are not realized and that unique cellular responses are limited to discrete subsets of ligands and pathways that enhance specific cellular functions.

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Year:  2009        PMID: 19454649      PMCID: PMC2711542          DOI: 10.1126/scisignal.2000054

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


  39 in total

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2.  Specificity and stability in topology of protein networks.

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3.  The use of RNA interference to analyze protein phosphatase function in mammalian cells.

Authors:  Iain Fraser; Wei Liu; Robert Rebres; Tamara Roach; Joelle Zavzavadjian; Leah Santat; Jamie Liu; Estelle Wall; Marc Mumby
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Review 4.  Data-driven modelling of signal-transduction networks.

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5.  Uncoupling of inflammatory chemokine receptors by IL-10: generation of functional decoys.

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Authors:  Kevin A Janes; John G Albeck; Lili X Peng; Peter K Sorger; Douglas A Lauffenburger; Michael B Yaffe
Journal:  Mol Cell Proteomics       Date:  2003-06-26       Impact factor: 5.911

7.  Essential role of MD-2 in LPS responsiveness and TLR4 distribution.

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8.  A protein interaction map of Drosophila melanogaster.

Authors:  L Giot; J S Bader; C Brouwer; A Chaudhuri; B Kuang; Y Li; Y L Hao; C E Ooi; B Godwin; E Vitols; G Vijayadamodar; P Pochart; H Machineni; M Welsh; Y Kong; B Zerhusen; R Malcolm; Z Varrone; A Collis; M Minto; S Burgess; L McDaniel; E Stimpson; F Spriggs; J Williams; K Neurath; N Ioime; M Agee; E Voss; K Furtak; R Renzulli; N Aanensen; S Carrolla; E Bickelhaupt; Y Lazovatsky; A DaSilva; J Zhong; C A Stanyon; R L Finley; K P White; M Braverman; T Jarvie; S Gold; M Leach; J Knight; R A Shimkets; M P McKenna; J Chant; J M Rothberg
Journal:  Science       Date:  2003-11-06       Impact factor: 47.728

9.  A map of the interactome network of the metazoan C. elegans.

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Journal:  Science       Date:  2004-01-02       Impact factor: 47.728

Review 10.  Adenosine: an endogenous regulator of innate immunity.

Authors:  György Haskó; Bruce N Cronstein
Journal:  Trends Immunol       Date:  2004-01       Impact factor: 16.687

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  20 in total

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Review 2.  Models of signalling networks - what cell biologists can gain from them and give to them.

Authors:  Kevin A Janes; Douglas A Lauffenburger
Journal:  J Cell Sci       Date:  2013-05-01       Impact factor: 5.285

Review 3.  Towards genome-scale signalling network reconstructions.

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4.  Paring down signaling complexity.

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5.  Cell type specificity of signaling: view from membrane receptors distribution and their downstream transduction networks.

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6.  Circuit-level input integration in bacterial gene regulation.

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Review 7.  Multiscale models of cell signaling.

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8.  TNF-insulin crosstalk at the transcription factor GATA6 is revealed by a model that links signaling and transcriptomic data tensors.

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9.  Mapping signaling pathway cross-talk in Drosophila cells.

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

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