Machine learning uncovers cell identity regulator by histone code

Conversion between cell types, e.g., by induced expression of master transcription factors, holds great promise for cellular therapy. Our ability to manipulate cell identity is constrained by incomplete information on cell identity genes (CIGs) and their expression regulation. Here, we develop CEFCI...

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Detalles Bibliográficos
Autores principales: Xia, Bo, Zhao, Dongyu, Wang, Guangyu, Zhang, Min, Lv, Jie, Tomoiaga, Alin S., Li, Yanqiang, Wang, Xin, Meng, Shu, Cooke, John P., Cao, Qi, Zhang, Lili, Chen, Kaifu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7264183/
https://www.ncbi.nlm.nih.gov/pubmed/32483223
http://dx.doi.org/10.1038/s41467-020-16539-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7264183/
https://www.ncbi.nlm.nih.gov/pubmed/32483223
http://dx.doi.org/10.1038/s41467-020-16539-4

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