Name
Abstract | ||
|---|---|---|
Our results showed that the MISC model improved the cell type classification and could be instrumental to study cellular heterogeneity. Overall, MISC is a robust missing data imputation model for single-cell RNA-seq data. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s12918-018-0638-y | BMC Systems Biology |
Keywords | Field | DocType |
False negative curve,Missing data,Single-cell RNA-seq,Zero-inflated model | Zero-inflated model,RNA,Biology,Binary classification,Pattern recognition,Regression analysis,Artificial intelligence,Imputation (statistics),Bioinformatics,Missing data,Missing data imputation | Journal |
Volume | Issue | ISSN |
12 | Suppl 7 | 1752-0509 |
Citations | PageRank | References |
2 | 0.64 | 4 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mary Qu Yang | 1 | 933 | 191.35 |
| Sherman M Weissman | 2 | 2 | 0.98 |
| William Yang | 3 | 36 | 5.82 |
| Jialing Zhang | 4 | 2 | 1.32 |
| Allon Canaann | 5 | 2 | 0.64 |
| Renchu Guan | 6 | 175 | 19.41 |