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MultiVI: deep generative model for the integration of multi-modal data
View ORCID ProfileTal Ashuach, Mariano I. Gabitto, Michael I. Jordan, Nir Yosef
doi: https://doi.org/10.1101/2021.08.20.457057
Tal Ashuach
1Center for Computational Biology, University of California, Berkeley, CA, USA
2Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
Mariano I. Gabitto
2Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
3Department of Statistics, University of California, Berkeley, Berkeley, CA, USA
Michael I. Jordan
2Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
3Department of Statistics, University of California, Berkeley, Berkeley, CA, USA
Nir Yosef
1Center for Computational Biology, University of California, Berkeley, CA, USA
2Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
4Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
5Chan Zuckerberg BioHub, San Francisco, CA, USA
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Posted August 20, 2021.
MultiVI: deep generative model for the integration of multi-modal data
Tal Ashuach, Mariano I. Gabitto, Michael I. Jordan, Nir Yosef
bioRxiv 2021.08.20.457057; doi: https://doi.org/10.1101/2021.08.20.457057
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