Integrative 'omic' approach towards understanding the nature of human diseases

Balkan Journal of Medical Genetics

Volumn 15, Issue SUPPL., 2012, Pages 45-50

  Peterlin, B ^a   Maver, A ^a  

^a UNIVERSITY MEDICAL CENTRE LJUBLJANA   (Slovenia)

Author keywords

Data integration; Genomics; High throughput technologies; Transcriptomics

Indexed keywords

BIOLOGICAL MARKER; MESSENGER RNA; MICRORNA; TRANSCRIPTOME;

BIOMICS; CELL LEVEL; CLINICAL DATA REPOSITORY; CONFERENCE PAPER; CPG ISLAND; DISEASES; EPIGENETICS; GENE EXPRESSION; GENE SEQUENCE; GENETIC ASSOCIATION; GENOME; GENOMICS; HUMAN; INFORMATION; INTEGRATOMICS; PATHOGENESIS; PROTEOMICS; STATISTICS; TECHNOLOGY; TRANSCRIPTOMICS;

EID: 84879747237     PISSN: None     EISSN: 13110160     Source Type: Journal    
DOI: 10.2478/v10034-012-0018-7     Document Type: Conference Paper

References (14)

1. Allison DB, Cui X, Page GP, Sabripour M. Microarray data analysis: from disarray to consolidation and consensus. Nat Rev Genet. 2006; 7(1): 55-65 (Pubitemid 41828948)
2. Schuster SC. Next-generation sequencing transforms today's biology. Nat Methods. 2008; 5(1): 16-18
3. Shi L, Reid LH, Jones WD, et al. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nat Biotechnol. 2006; 24(9): 1151- 1161. (Pubitemid 44359727)
4. Leinonen R, Sugawara H, Shumway M. The sequence read archive. Nucleic Acids Res. 2011; 39(Database issue): D19-D21
5. Leinonen R, Akhtar R, Birney E, et al. The European nucleotide archive. Nucleic Acids Res. 2011; 39 (Database issue): D28-D31
6. Parkinson H, Kapushesky M, Shojatalab M, et al. ArrayExpress-a public database of microarray experiments and gene expression profiles. Nucleic Acids Res. 2007; 35(Database issue): D747-D750 (Pubitemid 46056303)
7. Barrett T, Edgar R. Gene expression omnibus: microarray data storage, submission, retrieval, and analysis. Methods Enzymol. 2006; 411: 352-369 (Pubitemid 44291435)
8. Maver A, Peterlin B. Positional integratomic approach in identification of genomic candidate regions for Parkinson's disease. Bioinformatics. 2011; 27(14): 1971-1978
9. Breitling R, Herzyk P. Rank-based methods as a non-parametric alternative of the T-statistic for the analysis of biological microarray data. J Bioinform Comput Biol. 2005; 3(5): 1171-1189 (Pubitemid 41683435)
10. Kotera M, Hirakawa M, Tokimatsu T, Goto S, Kanehisa M. The KEGG databases and tools facilitating omics analysis: latest developments involving human diseases and pharmaceuticals. Methods Mol Biol. 2012; 802: 19-39
11. Obayashi T, Kinoshita K. COXPRESdb: a database to compare gene coexpression in seven model animals. Nucleic Acids Res. 2011; 39(Database issue): D1016-D1022
12. Sawcer S, Hellenthal G, Pirinen M, et al. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis. Nature. 2011; 476(7359?): 214-219
13. Manolio TA, Collins FS, Cox NJ, et al. Finding the missing heritability of complex diseases. Nature. 2009; 461(7265): 747-753
14. Marchini J, Donnelly P, Cardon LR. Genome-wide strategies for detecting multiple loci that influence complex diseases. Nat Genet. 2005; 37(4): 413-417.