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Cited by in F6Publishing
For: Zeng T, Dai H. Single-Cell RNA Sequencing-Based Computational Analysis to Describe Disease Heterogeneity. Front Genet 2019;10:629. [PMID: 31354786 DOI: 10.3389/fgene.2019.00629] [Cited by in Crossref: 10] [Cited by in F6Publishing: 10] [Article Influence: 5.0] [Reference Citation Analysis]
Number Citing Articles
1 [DOI: 10.1145/3368555.3384449] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
2 Wang Y, Wang JY, Schnieke A, Fischer K. Advances in single-cell sequencing: insights from organ transplantation. Mil Med Res 2021;8:45. [PMID: 34389057 DOI: 10.1186/s40779-021-00336-1] [Reference Citation Analysis]
3 Ramón Y Cajal S, Sesé M, Capdevila C, Aasen T, De Mattos-Arruda L, Diaz-Cano SJ, Hernández-Losa J, Castellví J. Clinical implications of intratumor heterogeneity: challenges and opportunities. J Mol Med (Berl) 2020;98:161-77. [PMID: 31970428 DOI: 10.1007/s00109-020-01874-2] [Cited by in Crossref: 55] [Cited by in F6Publishing: 53] [Article Influence: 55.0] [Reference Citation Analysis]
4 Yu X, Wang Z, Zeng T. Essential gene expression pattern of head and neck squamous cell carcinoma revealed by tumor-specific expression rule based on single-cell RNA sequencing. Biochim Biophys Acta Mol Basis Dis 2020;1866:165791. [PMID: 32234410 DOI: 10.1016/j.bbadis.2020.165791] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
5 Bigaeva E, Uniken Venema WTC, Weersma RK, Festen EAM. Understanding human gut diseases at single-cell resolution. Hum Mol Genet 2020;29:R51-8. [PMID: 32588873 DOI: 10.1093/hmg/ddaa130] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
6 Noé A, Cargill TN, Nielsen CM, Russell AJC, Barnes E. The Application of Single-Cell RNA Sequencing in Vaccinology. J Immunol Res 2020;2020:8624963. [PMID: 32802896 DOI: 10.1155/2020/8624963] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
7 Oprescu SN, Yue F, Qiu J, Brito LF, Kuang S. Temporal Dynamics and Heterogeneity of Cell Populations during Skeletal Muscle Regeneration. iScience 2020;23:100993. [PMID: 32248062 DOI: 10.1016/j.isci.2020.100993] [Cited by in Crossref: 23] [Cited by in F6Publishing: 17] [Article Influence: 23.0] [Reference Citation Analysis]
8 Zeng T, Yu X, Chen Z. Applying artificial intelligence in the microbiome for gastrointestinal diseases: A review. J Gastroenterol Hepatol 2021;36:832-40. [PMID: 33880762 DOI: 10.1111/jgh.15503] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
9 Nakajima KI, Guevara-Plunkett S, Chuang F, Wang KH, Lyu Y, Kumar A, Luxardi G, Izumiya C, Soulika A, Campbell M, Izumiya Y. Rainbow Kaposi's Sarcoma-Associated Herpesvirus Revealed Heterogenic Replication with Dynamic Gene Expression. J Virol 2020;94:e01565-19. [PMID: 31969436 DOI: 10.1128/JVI.01565-19] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 4.0] [Reference Citation Analysis]
10 Li J, Yu C, Ma L, Wang J, Guo G. Comparison of Scanpy-based algorithms to remove the batch effect from single-cell RNA-seq data. Cell Regen 2020;9:10. [PMID: 32632608 DOI: 10.1186/s13619-020-00041-9] [Cited by in F6Publishing: 1] [Reference Citation Analysis]