342 related articles for article (PubMed ID: 30758825)
1. Inference of Gene Co-expression Networks from Single-Cell RNA-Sequencing Data.
Lamere AT; Li J
Methods Mol Biol; 2019; 1935():141-153. PubMed ID: 30758825
[TBL] [Abstract][Full Text] [Related]
2. LEAP: constructing gene co-expression networks for single-cell RNA-sequencing data using pseudotime ordering.
Specht AT; Li J
Bioinformatics; 2017 Mar; 33(5):764-766. PubMed ID: 27993778
[TBL] [Abstract][Full Text] [Related]
3. Pseudotime Reconstruction Using TSCAN.
Ji Z; Ji H
Methods Mol Biol; 2019; 1935():115-124. PubMed ID: 30758823
[TBL] [Abstract][Full Text] [Related]
4. scPADGRN: A preconditioned ADMM approach for reconstructing dynamic gene regulatory network using single-cell RNA sequencing data.
Zheng X; Huang Y; Zou X
PLoS Comput Biol; 2020 Jul; 16(7):e1007471. PubMed ID: 32716923
[TBL] [Abstract][Full Text] [Related]
5. Network embedding-based representation learning for single cell RNA-seq data.
Li X; Chen W; Chen Y; Zhang X; Gu J; Zhang MQ
Nucleic Acids Res; 2017 Nov; 45(19):e166. PubMed ID: 28977434
[TBL] [Abstract][Full Text] [Related]
6. Inferring Causal Gene Regulatory Networks from Coupled Single-Cell Expression Dynamics Using Scribe.
Qiu X; Rahimzamani A; Wang L; Ren B; Mao Q; Durham T; McFaline-Figueroa JL; Saunders L; Trapnell C; Kannan S
Cell Syst; 2020 Mar; 10(3):265-274.e11. PubMed ID: 32135093
[TBL] [Abstract][Full Text] [Related]
7. A comprehensive survey of regulatory network inference methods using single cell RNA sequencing data.
Nguyen H; Tran D; Tran B; Pehlivan B; Nguyen T
Brief Bioinform; 2021 May; 22(3):. PubMed ID: 34020546
[TBL] [Abstract][Full Text] [Related]
8. Guidance for RNA-seq co-expression network construction and analysis: safety in numbers.
Ballouz S; Verleyen W; Gillis J
Bioinformatics; 2015 Jul; 31(13):2123-30. PubMed ID: 25717192
[TBL] [Abstract][Full Text] [Related]
9. Exploiting single-cell expression to characterize co-expression replicability.
Crow M; Paul A; Ballouz S; Huang ZJ; Gillis J
Genome Biol; 2016 May; 17():101. PubMed ID: 27165153
[TBL] [Abstract][Full Text] [Related]
10. Gene Regulatory Network Inference from Single-Cell Data Using Multivariate Information Measures.
Chan TE; Stumpf MPH; Babtie AC
Cell Syst; 2017 Sep; 5(3):251-267.e3. PubMed ID: 28957658
[TBL] [Abstract][Full Text] [Related]
11. Network Inference from Single-Cell Transcriptomic Data.
Todorov H; Cannoodt R; Saelens W; Saeys Y
Methods Mol Biol; 2019; 1883():235-249. PubMed ID: 30547403
[TBL] [Abstract][Full Text] [Related]
12. Identifying strengths and weaknesses of methods for computational network inference from single-cell RNA-seq data.
McCalla SG; Fotuhi Siahpirani A; Li J; Pyne S; Stone M; Periyasamy V; Shin J; Roy S
G3 (Bethesda); 2023 Mar; 13(3):. PubMed ID: 36626328
[TBL] [Abstract][Full Text] [Related]
13. Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.
Zhu M; Dahmen JL; Stacey G; Cheng J
BMC Bioinformatics; 2013 Sep; 14():278. PubMed ID: 24053776
[TBL] [Abstract][Full Text] [Related]
14. Building gene regulatory networks from scATAC-seq and scRNA-seq using Linked Self Organizing Maps.
Jansen C; Ramirez RN; El-Ali NC; Gomez-Cabrero D; Tegner J; Merkenschlager M; Conesa A; Mortazavi A
PLoS Comput Biol; 2019 Nov; 15(11):e1006555. PubMed ID: 31682608
[TBL] [Abstract][Full Text] [Related]
15. Evaluating methods of inferring gene regulatory networks highlights their lack of performance for single cell gene expression data.
Chen S; Mar JC
BMC Bioinformatics; 2018 Jun; 19(1):232. PubMed ID: 29914350
[TBL] [Abstract][Full Text] [Related]
16. PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data.
Song D; Li JJ
Genome Biol; 2021 Apr; 22(1):124. PubMed ID: 33926517
[TBL] [Abstract][Full Text] [Related]
17. Gene Regulatory Network Inference Using Convolutional Neural Networks from scRNA-seq Data.
Mao G; Pang Z; Zuo K; Liu J
J Comput Biol; 2023 May; 30(5):619-631. PubMed ID: 36877552
[TBL] [Abstract][Full Text] [Related]
18. A Bayesian framework for the inference of gene regulatory networks from time and pseudo-time series data.
Sanchez-Castillo M; Blanco D; Tienda-Luna IM; Carrion MC; Huang Y
Bioinformatics; 2018 Mar; 34(6):964-970. PubMed ID: 29028984
[TBL] [Abstract][Full Text] [Related]
19. Inference of Gene Coexpression Networks from Bulk-Based RNA-Sequencing Data.
Lamere AT
Methods Mol Biol; 2021; 2328():13-23. PubMed ID: 34251617
[TBL] [Abstract][Full Text] [Related]
20. Computational approaches for interpreting scRNA-seq data.
Rostom R; Svensson V; Teichmann SA; Kar G
FEBS Lett; 2017 Aug; 591(15):2213-2225. PubMed ID: 28524227
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
