195 related articles for article (PubMed ID: 33592820)
1. Screening of potential biomarkers for distinguishing between latent and active tuberculosis in children using bioinformatics analysis.
Shao M; Wu F; Zhang J; Dong J; Zhang H; Liu X; Liang S; Wu J; Zhang L; Zhang C; Zhang W
Medicine (Baltimore); 2021 Feb; 100(5):e23207. PubMed ID: 33592820
[TBL] [Abstract][Full Text] [Related]
2. Identification of Hub Genes in Tuberculosis via Bioinformatics Analysis.
Zhang T; Rao G; Gao X
Comput Math Methods Med; 2021; 2021():8159879. PubMed ID: 34671419
[TBL] [Abstract][Full Text] [Related]
3. Transcriptional Profiling and Deriving a Seven-Gene Signature That Discriminates Active and Latent Tuberculosis: An Integrative Bioinformatics Approach.
Natarajan S; Ranganathan M; Hanna LE; Tripathy S
Genes (Basel); 2022 Mar; 13(4):. PubMed ID: 35456421
[TBL] [Abstract][Full Text] [Related]
4. Identification of Significant Genes in HIV/TB via Bioinformatics Analysis.
Li X; Xie Y; Zhang D; Wang Y; Wu J; Sun X; Wu Q
Ann Clin Lab Sci; 2020 Sep; 50(5):600-610. PubMed ID: 33067206
[TBL] [Abstract][Full Text] [Related]
5. Monocyte-related gene biomarkers for latent and active tuberculosis.
Li Y; Deng Y; He J
Bioengineered; 2021 Dec; 12(2):10799-10811. PubMed ID: 34751089
[TBL] [Abstract][Full Text] [Related]
6. Autophagy-related molecular clusters identified as indicators for distinguishing active and latent TB infection in pediatric patients.
Yu Y; Hua J; Chen L
BMC Pediatr; 2024 Jun; 24(1):398. PubMed ID: 38890657
[TBL] [Abstract][Full Text] [Related]
7. Comprehensive analyses of potential key genes in active tuberculosis: A systematic review.
Chen J; Liu C; Liang T; Xu G; Zhang Z; Lu Z; Jiang J; Chen T; Li H; Huang S; Chen L; Sun X; Cen J; Zhan X
Medicine (Baltimore); 2021 Jul; 100(30):e26582. PubMed ID: 34397688
[TBL] [Abstract][Full Text] [Related]
8. Integrated bioinformatics analysis for the screening of hub genes and therapeutic drugs in ovarian cancer.
Yang D; He Y; Wu B; Deng Y; Wang N; Li M; Liu Y
J Ovarian Res; 2020 Jan; 13(1):10. PubMed ID: 31987036
[TBL] [Abstract][Full Text] [Related]
9. Identification of unique key genes and miRNAs in latent tuberculosis infection by network analysis.
Lin Y; Zhang Y; Yu H; Tian R; Wang G; Li F
Mol Immunol; 2019 Aug; 112():103-114. PubMed ID: 31082644
[TBL] [Abstract][Full Text] [Related]
10. Comparing tuberculosis gene signatures in malnourished individuals using the TBSignatureProfiler.
Johnson WE; Odom A; Cintron C; Muthaiah M; Knudsen S; Joseph N; Babu S; Lakshminarayanan S; Jenkins DF; Zhao Y; Nankya E; Horsburgh CR; Roy G; Ellner J; Sarkar S; Salgame P; Hochberg NS
BMC Infect Dis; 2021 Jan; 21(1):106. PubMed ID: 33482742
[TBL] [Abstract][Full Text] [Related]
11. Identification and analysis of key genes associated with acute myocardial infarction by integrated bioinformatics methods.
Guo S; Wu J; Zhou W; Liu X; Liu Y; Zhang J; Jia S; Li J; Wang H
Medicine (Baltimore); 2021 Apr; 100(15):e25553. PubMed ID: 33847684
[TBL] [Abstract][Full Text] [Related]
12. Identification and Verification of Potential Core Genes in Pediatric Septic Shock.
Xu Z; Jiang M; Bai X; Ding L; Dong P; Jiang M
Comb Chem High Throughput Screen; 2022; 25(13):2228-2239. PubMed ID: 35272594
[TBL] [Abstract][Full Text] [Related]
13. Identification of candidate biomarkers and pathways associated with SCLC by bioinformatics analysis.
Wen P; Chidanguro T; Shi Z; Gu H; Wang N; Wang T; Li Y; Gao J
Mol Med Rep; 2018 Aug; 18(2):1538-1550. PubMed ID: 29845250
[TBL] [Abstract][Full Text] [Related]
14. Comprehensive identification of immuno-related transcriptional signature for active pulmonary tuberculosis by integrated analysis of array and single cell RNA-seq.
Xu Y; Tan Y; Zhang X; Cheng M; Hu J; Liu J; Chen X; Zhu J
J Infect; 2022 Nov; 85(5):534-544. PubMed ID: 36007657
[TBL] [Abstract][Full Text] [Related]
15. Identification of Biomarkers for Sarcoidosis and Tuberculosis of the Lung Using Systematic and Integrated Analysis.
Zhao M; Di X; Jin X; Tian C; Cong S; Liu J; Wang K
Med Sci Monit; 2020 Jul; 26():e925438. PubMed ID: 32701935
[TBL] [Abstract][Full Text] [Related]
16. Identification of Core Genes and Pathways in Melanoma Metastasis via Bioinformatics Analysis.
Xie R; Li B; Jia L; Li Y
Int J Mol Sci; 2022 Jan; 23(2):. PubMed ID: 35054979
[TBL] [Abstract][Full Text] [Related]
17. Bioinformatics analyses of significant genes, related pathways and candidate prognostic biomarkers in glioblastoma.
Zhou L; Tang H; Wang F; Chen L; Ou S; Wu T; Xu J; Guo K
Mol Med Rep; 2018 Nov; 18(5):4185-4196. PubMed ID: 30132538
[TBL] [Abstract][Full Text] [Related]
18. Bioinformatics analysis of gene expression profile data to screen key genes involved in intracranial aneurysms.
Guo T; Hou D; Yu D
Mol Med Rep; 2019 Nov; 20(5):4415-4424. PubMed ID: 31545495
[TBL] [Abstract][Full Text] [Related]
19. Gene network in pulmonary tuberculosis based on bioinformatic analysis.
Li L; Lv J; He Y; Wang Z
BMC Infect Dis; 2020 Aug; 20(1):612. PubMed ID: 32811479
[TBL] [Abstract][Full Text] [Related]
20. Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Pediatric Sepsis.
Xie K; Kong S; Li F; Zhang Y; Wang J; Zhao W
Med Sci Monit; 2020 Jun; 26():e923881. PubMed ID: 32575108
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
