scMINER: a mutual information-based framework for identifying hidden drivers from single-cell omics data

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The sparse nature of single-cell omics data makes it challenging to dissect the wiring and rewiring of the transcriptional and signaling drivers that regulate cellular states. Many of the drivers, referred to as “hidden drivers”, are difficult to identify via conventional expression analysis due to...

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Detalles Bibliográficos
Autores principales: Ding, Liang, Shi, Hao, Qian, Chenxi, Burdyshaw, Chad, Veloso, Joao Pedro, Khatamian, Alireza, Pan, Qingfei, Dhungana, Yogesh, Xie, Zhen, Risch, Isabel, Yang, Xu, Huang, Xin, Yan, Lei, Rusch, Michael, Brewer, Michael, Yan, Koon-Kiu, Chi, Hongbo, Yu, Jiyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9901036/
https://www.ncbi.nlm.nih.gov/pubmed/36747874
http://dx.doi.org/10.21203/rs.3.rs-2476875/v1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9901036/
https://www.ncbi.nlm.nih.gov/pubmed/36747874
http://dx.doi.org/10.21203/rs.3.rs-2476875/v1

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