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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...
| Autores principales: | , , , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2020
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| Materias: | |
| 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 |