These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

167 related articles for article (PubMed ID: 34270548)

  • 1. Prioritizing and characterizing functionally relevant genes across human tissues.
    Somepalli G; Sahoo S; Singh A; Hannenhalli S
    PLoS Comput Biol; 2021 Jul; 17(7):e1009194. PubMed ID: 34270548
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Understanding Tissue-Specific Gene Regulation.
    Sonawane AR; Platig J; Fagny M; Chen CY; Paulson JN; Lopes-Ramos CM; DeMeo DL; Quackenbush J; Glass K; Kuijjer ML
    Cell Rep; 2017 Oct; 21(4):1077-1088. PubMed ID: 29069589
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Integrative Approaches for Inference of Genome-Scale Gene Regulatory Networks.
    Siahpirani AF; Chasman D; Roy S
    Methods Mol Biol; 2019; 1883():161-194. PubMed ID: 30547400
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Integrating transcriptional and protein interaction networks to prioritize condition-specific master regulators.
    Padi M; Quackenbush J
    BMC Syst Biol; 2015 Nov; 9():80. PubMed ID: 26576632
    [TBL] [Abstract][Full Text] [Related]  

  • 5. NetCore: a network propagation approach using node coreness.
    Barel G; Herwig R
    Nucleic Acids Res; 2020 Sep; 48(17):e98. PubMed ID: 32735660
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Influence of tissue context on gene prioritization for predicted transcriptome-wide association studies.
    Li B; Veturi Y; Bradford Y; Verma SS; Verma A; Lucas AM; Haas DW; Ritchie MD
    Pac Symp Biocomput; 2019; 24():296-307. PubMed ID: 30864331
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart disease.
    Liu Y; Bai F; Tang Z; Liu N; Liu Q
    BMC Cardiovasc Disord; 2021 Jan; 21(1):52. PubMed ID: 33509101
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules.
    Yao X; Yan J; Liu K; Kim S; Nho K; Risacher SL; Greene CS; Moore JH; Saykin AJ; Shen L;
    Bioinformatics; 2017 Oct; 33(20):3250-3257. PubMed ID: 28575147
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Prioritizing Crohn's disease genes by integrating association signals with gene expression implicates monocyte subsets.
    Gettler K; Giri M; Kenigsberg E; Martin J; Chuang LS; Hsu NY; Denson LA; Hyams JS; Griffiths A; Noe JD; Crandall WV; Mack DR; Kellermayer R; Abraham C; Hoffman G; Kugathasan S; Cho JH
    Genes Immun; 2019 Sep; 20(7):577-588. PubMed ID: 30692607
    [TBL] [Abstract][Full Text] [Related]  

  • 10. From SNP co-association to RNA co-expression: novel insights into gene networks for intramuscular fatty acid composition in porcine.
    Ramayo-Caldas Y; Ballester M; Fortes MR; Esteve-Codina A; Castelló A; Noguera JL; Fernández AI; Pérez-Enciso M; Reverter A; Folch JM
    BMC Genomics; 2014 Mar; 15():232. PubMed ID: 24666776
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A comprehensive survey for human transcription factors on expression, regulation, interaction, phenotype and cancer survival.
    Hu H; Zhang Q; Hu FF; Liu CJ; Guo AY
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33517372
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Investigating transcriptome-wide sex dimorphism by multi-level analysis of single-cell RNA sequencing data in ten mouse cell types.
    Lu T; Mar JC
    Biol Sex Differ; 2020 Nov; 11(1):61. PubMed ID: 33153500
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Pinpointing miRNA and genes enrichment over trait-relevant tissue network in Genome-Wide Association Studies.
    Li B; Dong J; Yu J; Fan Y; Shang L; Zhou X; Bai Y
    BMC Med Genomics; 2020 Dec; 13(Suppl 11):191. PubMed ID: 33371893
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases.
    Marbach D; Lamparter D; Quon G; Kellis M; Kutalik Z; Bergmann S
    Nat Methods; 2016 Apr; 13(4):366-70. PubMed ID: 26950747
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predicting distinct organization of transcription factor binding sites on the promoter regions: a new genome-based approach to expand human embryonic stem cell regulatory network.
    Hosseinpour B; Bakhtiarizadeh MR; Khosravi P; Ebrahimie E
    Gene; 2013 Dec; 531(2):212-9. PubMed ID: 24042128
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Gene expression profiling and bioinformatics analysis of gastric carcinoma.
    Liu N; Liu X; Zhou N; Wu Q; Zhou L; Li Q
    Exp Mol Pathol; 2014 Jun; 96(3):361-6. PubMed ID: 24589858
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks.
    Marbach D; Roy S; Ay F; Meyer PE; Candeias R; Kahveci T; Bristow CA; Kellis M
    Genome Res; 2012 Jul; 22(7):1334-49. PubMed ID: 22456606
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Modeling regulatory network topology improves genome-wide analyses of complex human traits.
    Zhu X; Duren Z; Wong WH
    Nat Commun; 2021 May; 12(1):2851. PubMed ID: 33990562
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A computational approach to identify cellular heterogeneity and tissue-specific gene regulatory networks.
    Jambusaria A; Klomp J; Hong Z; Rafii S; Dai Y; Malik AB; Rehman J
    BMC Bioinformatics; 2018 Jun; 19(1):217. PubMed ID: 29940845
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Pathway and network embedding methods for prioritizing psychiatric drugs.
    Pershad Y; Guo M; Altman RB
    Pac Symp Biocomput; 2020; 25():671-682. PubMed ID: 31797637
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.