scGNN 2.0: a graph neural network tool for imputation and clustering of single-cell RNA-Seq data is a research paper published in Bioinformatics (2022). On theSindex it has a DataRank of 0. It has been cited 26 times.
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National Institutes of Health
Grant: R01-131399
National Institutes of Health
Grant: U54-AG075931
National Institutes of Health
Grant: R35-GM126985
National Science Foundation
Grant: NSF1945971
NIA NIH HHS
Grant: U54 AG075931
NIGMS NIH HHS
Grant: R35 GM126985
NCI NIH HHS
Grant: P30 CA016058
National Institutes of Health
Grant: 5R01NS131399-03
Dissecting the Developmental and Epileptic Components of Encephalopathy in DEE
National Institutes of Health
Grant: 5R35GM126985-04
Interpretable and extendable deep learning model for biological sequence analysis and prediction
National Science Foundation
Grant: 1945971
EAGER: IIBR Informatics: A reinforced imputation framework for accurate gene expression recovery from single-cell RNA-seq data
FWCI
1.96
Citation Percentile
0.9%
Citation Trend
Fields of Study
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Sustainable Development Goals