ACTIVA : realistic single-cell RNA-seq generation with automatic cell-type identification using introspective variational autoencoders is a research paper published in Bioinformatics (2022). On theSindex it has a DataRank of 0. It has been cited 34 times.
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National Institutes of Health
Grant: R15-HL146779
National Institutes of Health
Grant: R01-GM126548
National Science Foundation
Grant: DMS-1840265
NHLBI NIH HHS
Grant: R15 HL146779
NIGMS NIH HHS
Grant: R01 GM126548
National Science Foundation
Grant: 1840265
RTG: Data-Intensive Research and Computing at the University of California, Merced
National Institutes of Health
Grant: 1R15HL146779-01
Experimental and mathematical modeling of CD8 T cell dynamics in autoimmune disease
National Institutes of Health
Grant: 5R01GM126548-04
Mathematical Strategies to Uncover the Molecular Basis of Prion Transitions
University of California Office of the President and University of California Merced COVID-19
FWCI
2.52
Citation Percentile
0.9%
Citation Trend
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