Cargando…
SingleCellSignalR: inference of intercellular networks from single-cell transcriptomics
Single-cell transcriptomics offers unprecedented opportunities to infer the ligand–receptor (LR) interactions underlying cellular networks. We introduce a new, curated LR database and a novel regularized score to perform such inferences. For the first time, we try to assess the confidence in predict...
Autores principales: | Cabello-Aguilar, Simon, Alame, Mélissa, Kon-Sun-Tack, Fabien, Fau, Caroline, Lacroix, Matthieu, Colinge, Jacques |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7261168/ https://www.ncbi.nlm.nih.gov/pubmed/32196115 http://dx.doi.org/10.1093/nar/gkaa183 |
Ejemplares similares
-
Cell lineage and communication network inference via optimization for single-cell transcriptomics
por: Wang, Shuxiong, et al.
Publicado: (2019) -
CellDART: cell type inference by domain adaptation of single-cell and spatial transcriptomic data
por: Bae, Sungwoo, et al.
Publicado: (2022) -
Inference of cell state transitions and cell fate plasticity from single-cell with MARGARET
por: Pandey, Kushagra, et al.
Publicado: (2022) -
Detecting critical transition signals from single-cell transcriptomes to infer lineage-determining transcription factors
por: Yang, Xinan H, et al.
Publicado: (2022) -
Single-cell gene regulation network inference by large-scale data integration
por: Dong, Xin, et al.
Publicado: (2022)