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Machine Learning of Stem Cell Identities From Single-Cell Expression Data via Regulatory Network Archetypes
The molecular regulatory network underlying stem cell pluripotency has been intensively studied, and we now have a reliable ensemble model for the “average” pluripotent cell. However, evidence of significant cell-to-cell variability suggests that the activity of this network varies within individual...
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| Publicado no: | Front Genet |
|---|---|
| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6349820/ https://ncbi.nlm.nih.gov/pubmed/30723489 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fgene.2019.00002 |
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