Name
Abstract | ||
|---|---|---|
The rapid development of single-cell RNA sequencing (scRNA-seq)technology reveals the gene expression status and gene structure of individual cells, reflecting the heterogeneity and diversity of cells. The traditional methods of scRNA-seq data analysis treat data as the same subspace, and hide structural information in other subspaces. In this paper, we propose a low-rank subspace ensemble cluster... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TCBB.2020.3029187 | IEEE/ACM Transactions on Computational Biology and Bioinformatics |
Keywords | DocType | Volume |
Clustering algorithms,Bioinformatics,Data models,Mathematical model,RNA,Sequential analysis,Periodic structures | Journal | 19 |
Issue | ISSN | Citations |
2 | 1545-5963 | 2 |
PageRank | References | Authors |
0.38 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| ChuanYuan Wang | 1 | 2 | 1.73 |
| Gao Ying-Lian | 2 | 29 | 18.73 |
| Liu Jin-Xing | 3 | 40 | 16.11 |
| Xiang-Zhen Kong | 4 | 2 | 0.38 |
| Chun-hou Zheng | 5 | 732 | 71.79 |