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Deciphering plant cell–cell communications using single-cell omics data

Plants have various cell types that respond to different environmental factors, and cell–cell communication is the fundamental process that controls these plant responses. The emergence of single-cell techniques provides opportunities to explore features unique to each cell type and construct a comp...

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Detalles Bibliográficos
Autores principales: Jin, Jingjing, Yu, Shizhou, Lu, Peng, Cao, Peijian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10412842/
https://www.ncbi.nlm.nih.gov/pubmed/37576747
http://dx.doi.org/10.1016/j.csbj.2023.06.016
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author Jin, Jingjing
Yu, Shizhou
Lu, Peng
Cao, Peijian
author_facet Jin, Jingjing
Yu, Shizhou
Lu, Peng
Cao, Peijian
author_sort Jin, Jingjing
collection PubMed
description Plants have various cell types that respond to different environmental factors, and cell–cell communication is the fundamental process that controls these plant responses. The emergence of single-cell techniques provides opportunities to explore features unique to each cell type and construct a comprehensive cell–cell communication (CCC) network. Although the most current successes of CCC inference were achieved in animal research, computational methods can also be directly applied to plants. This review describes the current major models for cell–cell communication inference and summarizes the computational tools based on single-cell omics datasets. In addition, we discuss the limitations of plant cell–cell communication research and propose new directions to expand the field in meaningful ways.
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spelling pubmed-104128422023-08-11 Deciphering plant cell–cell communications using single-cell omics data Jin, Jingjing Yu, Shizhou Lu, Peng Cao, Peijian Comput Struct Biotechnol J Mini-Review Plants have various cell types that respond to different environmental factors, and cell–cell communication is the fundamental process that controls these plant responses. The emergence of single-cell techniques provides opportunities to explore features unique to each cell type and construct a comprehensive cell–cell communication (CCC) network. Although the most current successes of CCC inference were achieved in animal research, computational methods can also be directly applied to plants. This review describes the current major models for cell–cell communication inference and summarizes the computational tools based on single-cell omics datasets. In addition, we discuss the limitations of plant cell–cell communication research and propose new directions to expand the field in meaningful ways. Research Network of Computational and Structural Biotechnology 2023-06-17 /pmc/articles/PMC10412842/ /pubmed/37576747 http://dx.doi.org/10.1016/j.csbj.2023.06.016 Text en © 2023 Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Mini-Review
Jin, Jingjing
Yu, Shizhou
Lu, Peng
Cao, Peijian
Deciphering plant cell–cell communications using single-cell omics data
title Deciphering plant cell–cell communications using single-cell omics data
title_full Deciphering plant cell–cell communications using single-cell omics data
title_fullStr Deciphering plant cell–cell communications using single-cell omics data
title_full_unstemmed Deciphering plant cell–cell communications using single-cell omics data
title_short Deciphering plant cell–cell communications using single-cell omics data
title_sort deciphering plant cell–cell communications using single-cell omics data
topic Mini-Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10412842/
https://www.ncbi.nlm.nih.gov/pubmed/37576747
http://dx.doi.org/10.1016/j.csbj.2023.06.016
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