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Articles relevant to functional genomics and proteomics

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Comment on the must read papers of the last 3-6 months:

A summary of a recent meeting about genome-wide studies of complex diseases addresses the huge challenges and possible solutions:

Petretto E, Aitman TJ. A gene harvest revealing the archeology and complexity of human disease. Nature Gen 2007; 39: 1299-3002

This study is a very elegant example of how integrated network-based analysis of high-throughput data from humans and model organisms as well as data from the public data can be used to identify new disease mechanisms, genes and polymorphisms:

Pujana et al. Network modeling links breast cancer susceptibility and centrosome dysfunction. Nat Genet. 2007;39:1338-1349

This article is a conceptually brilliant discussion about how different complex diseases can be described as nodes in network. The nodes are described both geno- and phenotypically and there is considerable overlap:

Barabasi AL. Network medicine--from obesity to the "diseasome".

N Engl J Med. 2007

Reviews

Microarrays/proteomics

Benson M, Cardell LO, Jernås M, Carlsson B, Reinholdt J, Svensson PA, Carlsson L. DNA microarrays to profile gene expression in allergic rhinitis. Clin Exp Allergy 2002; 31:301-8.

Pawliczak R, Shelhamer JH. Application of functional genomics in allergy and clinical immunology. Allergy. 2003;58:973-80.

Harwanegg C, Hiller R. Protein microarrays in diagnosing IgE-mediated diseases: spotting allergy at the molecular level. Expert Rev Mol Diagn 2004;4:539-48.

Systems biology

Alon U. Biological networks: the tinkerer as an engineer. Science 2003;301:1866-7.

Hood R.

Systems biology and new technologies enable predictive and preventative medicine.

Science 2004;306:640-3.

Original microarray articles

Selected microarray articles in fields other than allergy

Khan J, Wei JS, Ringner M, Saal LH, Ladanyi M, Westermann F, Berthold F, Schwab M, Antonescu CR, Peterson C, Meltzer PS. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat Med 2001;7:673-9.

Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, Boldrick JC, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature. 2000; 403:503-11.

Rhodes DR, Barrette TR, Rubin MA, Ghosh D, Chinnaiyan AM Meta-analysis of microarrays: interstudy validation of gene expression profiles reveals pathway dysregulation in prostate cancer. Cancer Res 2002;62:4427-33.

Shipp MA, Ross KN, Tamayo P, Weng AP, Kutok JL, Aguiar RC, Gaasenbeek et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nat Med. 2002;8:68-74.

Microarray articles in allergy/immunology research

Adner M, Zhang Y, Swärd K, Benson M, Lars Olaf Cardell. Up-regulation of 5-HT2A receptor-mediated contractile responses in mousetrachea following long-term exposure to TNFa. Brit J Pharmacol 2002; 137:971-82

Argyropoulos C, Nikiforidis GC, Theodoropoulou M, Adamopoulos P, Boubali S, et al. Mining microarray data to identify transcription factors expressed in naive resting but not activated T lymphocytes. Genes Immun 2004;5:16-25.

Benson M, Adner M, Jansson L, Lutz A, Uddman R, Cardell LO. Gene profiling reveals increased expression of uteroglobin and other anti-inflammatory genes in nasal fluid cells from patients with allergic rhinitis. Clin Exp Allergy 2005 (in press)

Benson M, Carlsson LM, Adner M, Jernås M, Rudemo M, Sjögren A, Uddman R Cardell LO. Gene profiling reveals increased expression of uteroglobin and other anti-inflammatory genes in nasal polyps after treatment with glucocorticoids. J Allergy and Clinical Immunology 2004;113:1137

Benson M, Svensson PA, Carlsson B, Carlsson L, Martinsson T, Rudemo M, Cardell.LO Combining linkage- and DNA microarray analysis to identify susceptibility genes in allergic disease. Acta Otolar 2004;124:813-819

Benson M Jernås, B Carlsson, J Reinholdt, PA Svensson, L Carlsson, LO Cardell. DNA microarray analysis of Transforming Growth Factor Beta and related transcripts in nasal biopsies from patients with allergic rhinitis. Cytokine. 2002;18:20-5

Benson M, Fransson M, Wennergren G, Cardell LO. Increased expression of Vascular Endothelial Growth Factor in seasonal allergic rhinitis. Cytokine 2002;20:268-73

Benson M, Olsson M, Rudemo M, Wennergren G, CardellLO. Pros and cons of microarray technology in allergy research.Clin Exp Allergy. 2004; 34:1001-6.

Brutsche MH, Joos L, Carlen Brutsche IE, Bissinger R, Tamm M, Custovic A, Woodcock A. Array-based diagnostic gene-expression score for atopy and asthma.J Allergy Clin Immunol 2002;109:271-3.

Fritz SB, Terrell JE, Conner ER, Kukowska-Latallo JF, Baker JR. Nasal mucosal gene expression in patients with allergic rhinitis with and without nasal polyps. J Allergy Clin Immunol 2003;112:1057-63.

Hakonarson H, Halapi E, Whelan R, Gulcher J, Stefansson K, Grunstein MM. Association between IL-1beta/TNF-alpha-induced glucocorticoid-sensitive changes in multiple gene expression and altered responsiveness in airway smooth muscle. Am J Respir Cell Mol Biol 2001;25:761-71.

Karp CL, Grupe A, Schadt E, Ewart SL, Keane-Moore M, Cuomo PJ, Kohl J, Wahl L, Kuperman D, Germer S, Aud D, Peltz G, Wills-Karp M. Identification of complement factor 5 as a susceptibility locus for experimental allergic asthma. Nat Immunol 2000;1:221-6.

Lee JH, Kaminski N, Dolganov G, Grunig G, Koth L, Solomon C, Erle DJ, Sheppard D. Interleukin-13 induces dramatically different transcriptional programs in three human airway cell types. Am J Respir Cell Mol Biol 2001; 25:474-85.

Lund R, Aittokallio T, Nevalainen O, Lahesmaa R. Identification of novel genes regulated by IL-12, IL-4, or TGF-beta during the early polarization of CD4+ lymphocytes. J Immunol 2003; 171:5328-36.

Nomura I, Gao B, Boguniewicz M, Darst MA, Travers JB, Leung DY Distinct patterns of gene expression in the skin lesions of atopic dermatitis and psoriasis: a gene microarray analysis. .J Allergy Clin Immunol 2003;112:1195-202.

Wohlfahrt JG, Kunzmann S, Menz G, Kneist W, Akdis CA, Blaser K, Schmidt-Weber CB. T cell phenotype in allergic asthma and atopic dermatitis. Int Arch Allergy Immunol 2003;131(4):272-82

Zimmermann N, King NE, Laporte J, Yang M, Mishra A, Pope SM, et al. Dissection of experimental asthma with DNA microarray analysis identifies arginase in asthma pathogenesis. J Clin Invest. 2003;111:1863-74.

Original proteomics articles

Selected articles in fields other than allergy

Petricoin EF, Ardekani AM, Hitt BA, Levine PJ, Fusaro VA, Steinberg SM, Mills GB, Simone C, Fishman DA, Kohn EC, Liotta LA. Use of proteomic patterns in serum to identify ovarian cancer. Lancet. 2002;359:572-7.

Allergy/immunology related articles

Bacarese-Hamilton T, Mezzasoma L, Ingham C, Ardizzoni A, Rossi R, Bistoni F, Crisanti A. Detection of allergen-specific IgE on microarrays by use of signal amplification techniques. Clin Chem. 2002;48:1367-70

Hiller R, Laffer S, Harwanegg C, Huber M, Schmidt WM, Twardosz A, Barletta B, Becker WM, Blaser K, Breiteneder H, Chapman M, Crameri R, Duchene M, Ferreira F, Fiebig H, Hoffmann-Sommergruber K, King TP, Kleber-Janke T, Kurup VP, Lehrer SB, Lidholm J, Muller U, Pini C, Reese G, Scheiner O, Scheynius A, Shen HD, Spitzauer S, Suck R, Swoboda I, Thomas W, Tinghino R, Van Hage-Hamsten M, Virtanen T, Kraft D, Muller MW, Valenta R. Microarrayed allergen molecules: diagnostic gatekeepers for allergy treatment. FASEB J. 2002;16:414-6.

Tam SW, Wiese R, Lee S, Gilmore J, Kumble KD. Simultaneous analysis of eight human Th1/Th2 cytokines using microarrays. J Immunol Methods 2002; 261:157-65.

Bioinformatics

Bolstad BM, Irizarry RA, Astrand M, Speed TP. A comparison of normalization methods for high density array data based on variance and bias. Bioinformatics 2003; 19:185-193.

Stoeckert CJ Jr, Causton HC, Ball CA. Microarray databases: standards and ontologies. Nat Genet 2002;32 Suppl:469-73.

Kooperberg C, Sipione S, LeBlanc ML, Strand AD, Cattaneo E, Olson JM. Evaluating test-statistics to select interesting genes in microarray experiments. Human Molecular Genetics. 2002; 11:2223-32,

Dahlquist KD, Salomonis N, Vranizan K, Lawlor SC, Conklin BR. GenMAPP, a new tool for viewing and analyzing microarray data on biological pathways. Nat Genet 2002; 31:19-20

Jenssen TK, Laegreid A, Komorowski J, Hovig E.. A literature network of human genes for high-throughput analysis of gene expression. Nat Genet 2001;28:21-8.

Chuaqui RF, Bonner RF, Best CJ, Gillespie JW, Flaig MJ, Hewitt SM, Phillips JL, Krizman DB, Tangrea MA, Ahram M, Linehan WM, Knezevic V, Emmert-Buck MR. Post-analysis follow-up and validation of microarray experiments. Nat Genet 2002; 32 Suppl:509-14

Public databases for microarray experiments

Entrez is a linked system of databases to find information about individual genes and literature references (http://www.ncbi.nlm.nih.gov/). One of the databases, Omnibus, contains freely searchable data from more than 500 microarray experiments (http://www.ncbi.nlm.nih.gov/geo/)

BASE (http://base.thep.lu.se/) aims to provide all the tools needed for data storage, quality control, normalization and statistical application in a web-based application (Lao).

Minimum information about a microarray experiment – MIAME gives standards for microarray experiments are described at (http://www.mged.org/Workgroups/MIAME/miame.html)

The Gene Ontology Consortium and Pubgene and provides tools for automated grouping of functionally related genes (http://www.geneontology.org, http://www.pubgene.org/). GenMAPP may be used to identify activated biological pathways in gene expression data (http://www.genmapp.org/)