587 related articles for article (PubMed ID: 30304022)
1. CaSTLe - Classification of single cells by transfer learning: Harnessing the power of publicly available single cell RNA sequencing experiments to annotate new experiments.
Lieberman Y; Rokach L; Shay T
PLoS One; 2018; 13(10):e0205499. PubMed ID: 30304022
[TBL] [Abstract][Full Text] [Related]
2. A multitask clustering approach for single-cell RNA-seq analysis in Recessive Dystrophic Epidermolysis Bullosa.
Zhang H; Lee CAA; Li Z; Garbe JR; Eide CR; Petegrosso R; Kuang R; Tolar J
PLoS Comput Biol; 2018 Apr; 14(4):e1006053. PubMed ID: 29630593
[TBL] [Abstract][Full Text] [Related]
3. On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data.
Ng GYL; Tan SC; Ong CS
PLoS One; 2023; 18(10):e0292961. PubMed ID: 37856458
[TBL] [Abstract][Full Text] [Related]
4. Evaluation of single-cell classifiers for single-cell RNA sequencing data sets.
Zhao X; Wu S; Fang N; Sun X; Fan J
Brief Bioinform; 2020 Sep; 21(5):1581-1595. PubMed ID: 31675098
[TBL] [Abstract][Full Text] [Related]
5. JingleBells: A Repository of Immune-Related Single-Cell RNA-Sequencing Datasets.
Ner-Gaon H; Melchior A; Golan N; Ben-Haim Y; Shay T
J Immunol; 2017 May; 198(9):3375-3379. PubMed ID: 28416714
[TBL] [Abstract][Full Text] [Related]
6. A hybrid deep clustering approach for robust cell type profiling using single-cell RNA-seq data.
Srinivasan S; Leshchyk A; Johnson NT; Korkin D
RNA; 2020 Oct; 26(10):1303-1319. PubMed ID: 32532794
[TBL] [Abstract][Full Text] [Related]
7. Data Analysis in Single-Cell Transcriptome Sequencing.
Gao S
Methods Mol Biol; 2018; 1754():311-326. PubMed ID: 29536451
[TBL] [Abstract][Full Text] [Related]
8. DIMM-SC: a Dirichlet mixture model for clustering droplet-based single cell transcriptomic data.
Sun Z; Wang T; Deng K; Wang XF; Lafyatis R; Ding Y; Hu M; Chen W
Bioinformatics; 2018 Jan; 34(1):139-146. PubMed ID: 29036318
[TBL] [Abstract][Full Text] [Related]
9. Random forest based similarity learning for single cell RNA sequencing data.
Pouyan MB; Kostka D
Bioinformatics; 2018 Jul; 34(13):i79-i88. PubMed ID: 29950006
[TBL] [Abstract][Full Text] [Related]
10. Using transfer learning from prior reference knowledge to improve the clustering of single-cell RNA-Seq data.
Mieth B; Hockley JRF; Görnitz N; Vidovic MM; Müller KR; Gutteridge A; Ziemek D
Sci Rep; 2019 Dec; 9(1):20353. PubMed ID: 31889137
[TBL] [Abstract][Full Text] [Related]
11. Single-Cell RNA Sequencing Analysis: A Step-by-Step Overview.
Slovin S; Carissimo A; Panariello F; Grimaldi A; Bouché V; Gambardella G; Cacchiarelli D
Methods Mol Biol; 2021; 2284():343-365. PubMed ID: 33835452
[TBL] [Abstract][Full Text] [Related]
12. Machine learning and statistical methods for clustering single-cell RNA-sequencing data.
Petegrosso R; Li Z; Kuang R
Brief Bioinform; 2020 Jul; 21(4):1209-1223. PubMed ID: 31243426
[TBL] [Abstract][Full Text] [Related]
13. Clustering and classification methods for single-cell RNA-sequencing data.
Qi R; Ma A; Ma Q; Zou Q
Brief Bioinform; 2020 Jul; 21(4):1196-1208. PubMed ID: 31271412
[TBL] [Abstract][Full Text] [Related]
14. TSEE: an elastic embedding method to visualize the dynamic gene expression patterns of time series single-cell RNA sequencing data.
An S; Ma L; Wan L
BMC Genomics; 2019 Apr; 20(Suppl 2):224. PubMed ID: 30967106
[TBL] [Abstract][Full Text] [Related]
15. scNPF: an integrative framework assisted by network propagation and network fusion for preprocessing of single-cell RNA-seq data.
Ye W; Ji G; Ye P; Long Y; Xiao X; Li S; Su Y; Wu X
BMC Genomics; 2019 May; 20(1):347. PubMed ID: 31068142
[TBL] [Abstract][Full Text] [Related]
16. A machine learning-based method for automatically identifying novel cells in annotating single-cell RNA-seq data.
Li Z; Wang Y; Ganan-Gomez I; Colla S; Do KA
Bioinformatics; 2022 Oct; 38(21):4885-4892. PubMed ID: 36083008
[TBL] [Abstract][Full Text] [Related]
17. Dimension Reduction and Clustering Models for Single-Cell RNA Sequencing Data: A Comparative Study.
Feng C; Liu S; Zhang H; Guan R; Li D; Zhou F; Liang Y; Feng X
Int J Mol Sci; 2020 Mar; 21(6):. PubMed ID: 32235704
[TBL] [Abstract][Full Text] [Related]
18. Scalable preprocessing for sparse scRNA-seq data exploiting prior knowledge.
Mukherjee S; Zhang Y; Fan J; Seelig G; Kannan S
Bioinformatics; 2018 Jul; 34(13):i124-i132. PubMed ID: 29949988
[TBL] [Abstract][Full Text] [Related]
19. CTISL: a dynamic stacking multi-class classification approach for identifying cell types from single-cell RNA-seq data.
Wang X; Chai Z; Li S; Liu Y; Li C; Jiang Y; Liu Q
Bioinformatics; 2024 Feb; 40(2):. PubMed ID: 38317054
[TBL] [Abstract][Full Text] [Related]
20. A Single-Cell Sequencing Guide for Immunologists.
See P; Lum J; Chen J; Ginhoux F
Front Immunol; 2018; 9():2425. PubMed ID: 30405621
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
