Literature DB >> 33619299

Network analysis of the immune state of mice.

Elohim Fonseca Dos Reis1, Mark Viney2, Naoki Masuda3,4,5.   

Abstract

The mammalian immune system protects individuals from infection and disease. It is a complex system of interacting cells and molecules, which has been studied extensively to investigate its detailed function, principally using laboratory mice. Despite the complexity of the immune system, it is often analysed using a restricted set of immunological parameters. Here we have sought to generate a system-wide view of the murine immune response, which we have done by undertaking a network analysis of 120 immune measures. To date, there has only been limited network analyses of the immune system. Our network analysis identified a relatively low number of communities of immune measure nodes. Some of these communities recapitulate the well-known T helper 1 vs. T helper 2 cytokine polarisation (where ordination analyses failed to do so), which validates the utility of our approach. Other communities we detected show apparently novel juxtapositions of immune nodes. We suggest that the structure of these other communities might represent functional immunological units, which may require further empirical investigation. These results show the utility of network analysis in understanding the functioning of the mammalian immune system.

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Year:  2021        PMID: 33619299      PMCID: PMC7900184          DOI: 10.1038/s41598-021-83139-7

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  30 in total

1.  An approach to modelling in immunology.

Authors:  A Yates; C C Chan; R E Callard; A J George; J Stark
Journal:  Brief Bioinform       Date:  2001-09       Impact factor: 11.622

Review 2.  Network biology: understanding the cell's functional organization.

Authors:  Albert-László Barabási; Zoltán N Oltvai
Journal:  Nat Rev Genet       Date:  2004-02       Impact factor: 53.242

3.  On the use of correlation as a measure of network connectivity.

Authors:  Andrew Zalesky; Alex Fornito; Ed Bullmore
Journal:  Neuroimage       Date:  2012-02-11       Impact factor: 6.556

Review 4.  Scale-free networks in cell biology.

Authors:  Réka Albert
Journal:  J Cell Sci       Date:  2005-11-01       Impact factor: 5.285

5.  Weight-conserving characterization of complex functional brain networks.

Authors:  Mikail Rubinov; Olaf Sporns
Journal:  Neuroimage       Date:  2011-04-01       Impact factor: 6.556

6.  Configuration model for correlation matrices preserving the node strength.

Authors:  Naoki Masuda; Sadamori Kojaku; Yukie Sano
Journal:  Phys Rev E       Date:  2018-07       Impact factor: 2.529

Review 7.  Appearances can be deceiving: phenotypes of knockout mice.

Authors:  Ivana Barbaric; Gaynor Miller; T Neil Dear
Journal:  Brief Funct Genomic Proteomic       Date:  2007-06-20

Review 8.  The Immunology of Wild Rodents: Current Status and Future Prospects.

Authors:  Mark Viney; Eleanor M Riley
Journal:  Front Immunol       Date:  2017-11-14       Impact factor: 7.561

9.  Clustering Coefficients for Correlation Networks.

Authors:  Naoki Masuda; Michiko Sakaki; Takahiro Ezaki; Takamitsu Watanabe
Journal:  Front Neuroinform       Date:  2018-03-15       Impact factor: 4.081

10.  The comparative immunology of wild and laboratory mice, Mus musculus domesticus.

Authors:  Stephen Abolins; Elizabeth C King; Luke Lazarou; Laura Weldon; Louise Hughes; Paul Drescher; John G Raynes; Julius C R Hafalla; Mark E Viney; Eleanor M Riley
Journal:  Nat Commun       Date:  2017-05-03       Impact factor: 14.919

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