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