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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2023
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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 |
Sumario: | 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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