BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

293 related articles for article (PubMed ID: 18986552)

  • 1. Integrated weighted gene co-expression network analysis with an application to chronic fatigue syndrome.
    Presson AP; Sobel EM; Papp JC; Suarez CJ; Whistler T; Rajeevan MS; Vernon SD; Horvath S
    BMC Syst Biol; 2008 Nov; 2():95. PubMed ID: 18986552
    [TBL] [Abstract][Full Text] [Related]  

  • 2. An integrated approach to infer causal associations among gene expression, genotype variation, and disease.
    Lee E; Cho S; Kim K; Park T
    Genomics; 2009 Oct; 94(4):269-77. PubMed ID: 19540336
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Weighted gene co-expression network analysis identifies specific modules and hub genes related to coronary artery disease.
    Liu J; Jing L; Tu X
    BMC Cardiovasc Disord; 2016 Mar; 16():54. PubMed ID: 26944061
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Weighted Interaction SNP Hub (WISH) network method for building genetic networks for complex diseases and traits using whole genome genotype data.
    Kogelman LJ; Kadarmideen HN
    BMC Syst Biol; 2014; 8 Suppl 2(Suppl 2):S5. PubMed ID: 25032480
    [TBL] [Abstract][Full Text] [Related]  

  • 5. WGCNA: an R package for weighted correlation network analysis.
    Langfelder P; Horvath S
    BMC Bioinformatics; 2008 Dec; 9():559. PubMed ID: 19114008
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Gene Expression Factor Analysis to Differentiate Pathways Linked to Fibromyalgia, Chronic Fatigue Syndrome, and Depression in a Diverse Patient Sample.
    Iacob E; Light AR; Donaldson GW; Okifuji A; Hughen RW; White AT; Light KC
    Arthritis Care Res (Hoboken); 2016 Jan; 68(1):132-40. PubMed ID: 26097208
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Identification of candidate target genes for human peripheral arterial disease using weighted gene co‑expression network analysis.
    Yin DX; Zhao HM; Sun DJ; Yao J; Ding DY
    Mol Med Rep; 2015 Dec; 12(6):8107-12. PubMed ID: 26498853
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Identification of common regulators of genes in co-expression networks affecting muscle and meat properties.
    Ponsuksili S; Siengdee P; Du Y; Trakooljul N; Murani E; Schwerin M; Wimmers K
    PLoS One; 2015; 10(4):e0123678. PubMed ID: 25875247
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Characterization of Genetic Networks Associated with Alzheimer's Disease.
    Zhang B; Tran L; Emilsson V; Zhu J
    Methods Mol Biol; 2016; 1303():459-77. PubMed ID: 26235085
    [TBL] [Abstract][Full Text] [Related]  

  • 10. [WGCNA screening of prognostic markers in medulloblastoma].
    Du BS; Yuan L; Sun LG; Zhang ZY
    Zhonghua Yi Xue Za Zhi; 2020 Feb; 100(6):460-464. PubMed ID: 32146771
    [No Abstract]   [Full Text] [Related]  

  • 11. Dysregulated mechanisms underlying Duchenne muscular dystrophy from co-expression network preservation analysis.
    Mukund K; Subramaniam S
    BMC Res Notes; 2015 May; 8():182. PubMed ID: 25935398
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Systems biology of ovine intestinal parasite resistance: disease gene modules and biomarkers.
    Kadarmideen HN; Watson-Haigh NS; Andronicos NM
    Mol Biosyst; 2011 Jan; 7(1):235-46. PubMed ID: 21072409
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Gene expression profile exploration of a large dataset on chronic fatigue syndrome.
    Fang H; Xie Q; Boneva R; Fostel J; Perkins R; Tong W
    Pharmacogenomics; 2006 Apr; 7(3):429-40. PubMed ID: 16610953
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Identification of prognostic markers of high grade prostate cancer through an integrated bioinformatics approach.
    Huang H; Zhang Q; Ye C; Lv JM; Liu X; Chen L; Wu H; Yin L; Cui XG; Xu DF; Liu WH
    J Cancer Res Clin Oncol; 2017 Dec; 143(12):2571-2579. PubMed ID: 28849390
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Pathway analysis for a genome-wide association study of pneumoconiosis.
    Wang T; Yang J; Ji X; Chu M; Zhang R; Dai J; Jin G; Hu Z; Shen H; Ni C
    Toxicol Lett; 2015 Jan; 232(1):284-92. PubMed ID: 25445010
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Systematic analysis of microarray datasets to identify Parkinson's disease‑associated pathways and genes.
    Feng Y; Wang X
    Mol Med Rep; 2017 Mar; 15(3):1252-1262. PubMed ID: 28098893
    [TBL] [Abstract][Full Text] [Related]  

  • 17. [Identification and application of marker genes for differential diagnosis of chronic fatigue syndrome].
    Kawai T; Rokutan K
    Nihon Rinsho; 2007 Jun; 65(6):1029-33. PubMed ID: 17561693
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Prediction of complex human diseases from pathway-focused candidate markers by joint estimation of marker effects: case of chronic fatigue syndrome.
    Bhattacharjee M; Rajeevan MS; Sillanpää MJ
    Hum Genomics; 2015 Jun; 9(1):8. PubMed ID: 26063326
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A systems approach to the biology of mood disorders through network analysis of candidate genes.
    Detera-Wadleigh SD; Akula N
    Pharmacopsychiatry; 2011 May; 44 Suppl 1():S35-42. PubMed ID: 21547870
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An information theoretic method for reconstructing local regulatory network modules from polymorphic samples.
    Jagalur M; Kulp D
    Comput Syst Bioinformatics Conf; 2007; 6():133-43. PubMed ID: 17951819
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.