Inference and analysis of cell-cell communication using CellChat

Single-cell methods record molecule expressions of cells in a given tissue, but understanding interactions between cells remains challenging. Here the authors show by applying systems biology and machine learning approaches that they can infer and analyze cell-cell communication networks in an easil...

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Autores principales:	Suoqin Jin, Christian F. Guerrero-Juarez, Lihua Zhang, Ivan Chang, Raul Ramos, Chen-Hsiang Kuan, Peggy Myung, Maksim V. Plikus, Qing Nie
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/eac776c8aeed43009b282c2dd2c6db3b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

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spelling	oai:doaj.org-article:eac776c8aeed43009b282c2dd2c6db3b2021-12-02T14:21:27ZInference and analysis of cell-cell communication using CellChat10.1038/s41467-021-21246-92041-1723https://doaj.org/article/eac776c8aeed43009b282c2dd2c6db3b2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-21246-9https://doaj.org/toc/2041-1723Single-cell methods record molecule expressions of cells in a given tissue, but understanding interactions between cells remains challenging. Here the authors show by applying systems biology and machine learning approaches that they can infer and analyze cell-cell communication networks in an easily interpretable way.Suoqin JinChristian F. Guerrero-JuarezLihua ZhangIvan ChangRaul RamosChen-Hsiang KuanPeggy MyungMaksim V. PlikusQing NieNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-20 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Suoqin Jin Christian F. Guerrero-Juarez Lihua Zhang Ivan Chang Raul Ramos Chen-Hsiang Kuan Peggy Myung Maksim V. Plikus Qing Nie Inference and analysis of cell-cell communication using CellChat
description	Single-cell methods record molecule expressions of cells in a given tissue, but understanding interactions between cells remains challenging. Here the authors show by applying systems biology and machine learning approaches that they can infer and analyze cell-cell communication networks in an easily interpretable way.
format	article
author	Suoqin Jin Christian F. Guerrero-Juarez Lihua Zhang Ivan Chang Raul Ramos Chen-Hsiang Kuan Peggy Myung Maksim V. Plikus Qing Nie
author_facet	Suoqin Jin Christian F. Guerrero-Juarez Lihua Zhang Ivan Chang Raul Ramos Chen-Hsiang Kuan Peggy Myung Maksim V. Plikus Qing Nie
author_sort	Suoqin Jin
title	Inference and analysis of cell-cell communication using CellChat
title_short	Inference and analysis of cell-cell communication using CellChat
title_full	Inference and analysis of cell-cell communication using CellChat
title_fullStr	Inference and analysis of cell-cell communication using CellChat
title_full_unstemmed	Inference and analysis of cell-cell communication using CellChat
title_sort	inference and analysis of cell-cell communication using cellchat
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/eac776c8aeed43009b282c2dd2c6db3b
work_keys_str_mv	AT suoqinjin inferenceandanalysisofcellcellcommunicationusingcellchat AT christianfguerrerojuarez inferenceandanalysisofcellcellcommunicationusingcellchat AT lihuazhang inferenceandanalysisofcellcellcommunicationusingcellchat AT ivanchang inferenceandanalysisofcellcellcommunicationusingcellchat AT raulramos inferenceandanalysisofcellcellcommunicationusingcellchat AT chenhsiangkuan inferenceandanalysisofcellcellcommunicationusingcellchat AT peggymyung inferenceandanalysisofcellcellcommunicationusingcellchat AT maksimvplikus inferenceandanalysisofcellcellcommunicationusingcellchat AT qingnie inferenceandanalysisofcellcellcommunicationusingcellchat
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Inference and analysis of cell-cell communication using CellChat

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