A machine learning approach for the identification of key markers involved in brain development from single-cell transcriptomic data

BACKGROUND: The ability to sequence the transcriptomes of single cells using single-cell RNA-seq sequencing technologies presents a shift in the scientific paradigm where scientists, now, are able to concurrently investigate the complex biology of a heterogeneous population of cells, one at a time....

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Detalles Bibliográficos
Autores principales: Hu, Yongli, Hase, Takeshi, Li, Hui Peng, Prabhakar, Shyam, Kitano, Hiroaki, Ng, See Kiong, Ghosh, Samik, Wee, Lawrence Jin Kiat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5260093/
https://www.ncbi.nlm.nih.gov/pubmed/28155657
http://dx.doi.org/10.1186/s12864-016-3317-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5260093/
https://www.ncbi.nlm.nih.gov/pubmed/28155657
http://dx.doi.org/10.1186/s12864-016-3317-7

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