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Profiling Cell Signaling Networks at Single-cell Resolution

Signaling networks process intra- and extracellular information to modulate the functions of a cell. Deregulation of signaling networks results in abnormal cellular physiological states and often drives diseases. Network responses to a stimulus or a drug treatment can be highly heterogeneous across...

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Detalles Bibliográficos
Autores principales: Lun, Xiao-Kang, Bodenmiller, Bernd
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Biochemistry and Molecular Biology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196580/
https://www.ncbi.nlm.nih.gov/pubmed/32132232
http://dx.doi.org/10.1074/mcp.R119.001790
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author Lun, Xiao-Kang
Bodenmiller, Bernd
author_facet Lun, Xiao-Kang
Bodenmiller, Bernd
author_sort Lun, Xiao-Kang
collection PubMed
description Signaling networks process intra- and extracellular information to modulate the functions of a cell. Deregulation of signaling networks results in abnormal cellular physiological states and often drives diseases. Network responses to a stimulus or a drug treatment can be highly heterogeneous across cells in a tissue because of many sources of cellular genetic and non-genetic variance. Signaling network heterogeneity is the key to many biological processes, such as cell differentiation and drug resistance. Only recently, the emergence of multiplexed single-cell measurement technologies has made it possible to evaluate this heterogeneity. In this review, we categorize currently established single-cell signaling network profiling approaches by their methodology, coverage, and application, and we discuss the advantages and limitations of each type of technology. We also describe the available computational tools for network characterization using single-cell data and discuss potential confounding factors that need to be considered in single-cell signaling network analyses.
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spelling pubmed-71965802020-05-13 Profiling Cell Signaling Networks at Single-cell Resolution Lun, Xiao-Kang Bodenmiller, Bernd Mol Cell Proteomics Reviews Signaling networks process intra- and extracellular information to modulate the functions of a cell. Deregulation of signaling networks results in abnormal cellular physiological states and often drives diseases. Network responses to a stimulus or a drug treatment can be highly heterogeneous across cells in a tissue because of many sources of cellular genetic and non-genetic variance. Signaling network heterogeneity is the key to many biological processes, such as cell differentiation and drug resistance. Only recently, the emergence of multiplexed single-cell measurement technologies has made it possible to evaluate this heterogeneity. In this review, we categorize currently established single-cell signaling network profiling approaches by their methodology, coverage, and application, and we discuss the advantages and limitations of each type of technology. We also describe the available computational tools for network characterization using single-cell data and discuss potential confounding factors that need to be considered in single-cell signaling network analyses. The American Society for Biochemistry and Molecular Biology 2020-05 2020-03-04 /pmc/articles/PMC7196580/ /pubmed/32132232 http://dx.doi.org/10.1074/mcp.R119.001790 Text en © 2020 Lun and Bodenmiller. Author's Choice—Final version open access under the terms of the Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0) .
spellingShingle Reviews
Lun, Xiao-Kang
Bodenmiller, Bernd
Profiling Cell Signaling Networks at Single-cell Resolution
title Profiling Cell Signaling Networks at Single-cell Resolution
title_full Profiling Cell Signaling Networks at Single-cell Resolution
title_fullStr Profiling Cell Signaling Networks at Single-cell Resolution
title_full_unstemmed Profiling Cell Signaling Networks at Single-cell Resolution
title_short Profiling Cell Signaling Networks at Single-cell Resolution
title_sort profiling cell signaling networks at single-cell resolution
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196580/
https://www.ncbi.nlm.nih.gov/pubmed/32132232
http://dx.doi.org/10.1074/mcp.R119.001790
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