VoPo leverages cellular heterogeneity for predictive modeling of single-cell data

High-throughput single-cell analysis technologies produce an abundance of data that is critical for profiling the heterogeneity of cellular systems. We introduce VoPo (https://github.com/stanleyn/VoPo), a machine learning algorithm for predictive modeling and comprehensive visualization of the heter...

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Detalles Bibliográficos
Autores principales: Stanley, Natalie, Stelzer, Ina A., Tsai, Amy S., Fallahzadeh, Ramin, Ganio, Edward, Becker, Martin, Phongpreecha, Thanaphong, Nassar, Huda, Ghaemi, Sajjad, Maric, Ivana, Culos, Anthony, Chang, Alan L., Xenochristou, Maria, Han, Xiaoyuan, Espinosa, Camilo, Rumer, Kristen, Peterson, Laura, Verdonk, Franck, Gaudilliere, Dyani, Tsai, Eileen, Feyaerts, Dorien, Einhaus, Jakob, Ando, Kazuo, Wong, Ronald J., Obermoser, Gerlinde, Shaw, Gary M., Stevenson, David K., Angst, Martin S., Gaudilliere, Brice, Aghaeepour, Nima
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/PMC7385162/
https://www.ncbi.nlm.nih.gov/pubmed/32719375
http://dx.doi.org/10.1038/s41467-020-17569-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7385162/
https://www.ncbi.nlm.nih.gov/pubmed/32719375
http://dx.doi.org/10.1038/s41467-020-17569-8

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