Unsupervised generative and graph representation learning for modelling cell differentiation

Using machine learning techniques to build representations from biomedical data can help us understand the latent biological mechanism of action and lead to important discoveries. Recent developments in single-cell RNA-sequencing protocols have allowed measuring gene expression for individual cells...

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Detalles Bibliográficos
Autores principales: Bica, Ioana, Andrés-Terré, Helena, Cvejic, Ana, Liò, Pietro
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/PMC7300092/
https://www.ncbi.nlm.nih.gov/pubmed/32555334
http://dx.doi.org/10.1038/s41598-020-66166-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7300092/
https://www.ncbi.nlm.nih.gov/pubmed/32555334
http://dx.doi.org/10.1038/s41598-020-66166-8

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