Literature DB >> 21299687

Applying gene expression microarrays to pulmonary disease.

Joshua D Campbell1, Avrum Spira, Marc E Lenburg.   

Abstract

Gene expression microarrays are high throughput technologies that can simultaneously measure the expression levels of most known genes in the human genome within a biological sample. The study of gene expression has revealed new understanding into the biological complexities of the cell and can impact the field of medicine by providing new insights into disease. Examining gene expression in samples from patients with pulmonary disease can elucidate molecular mechanisms responsible for disease pathogenesis or uncover novel molecular subtypes within a disease. Gene expression signatures of disease pathogenesis can further be used to suggest novel therapeutic compounds. Biomarkers can be developed from gene expression data that can aid clinicians in diagnosing disease or can guide clinicians in tailoring therapeutic strategies to individual patients. To demonstrate the applications of gene expression microarray technology, we will review several studies in pulmonary disease that utilize gene expression profiling techniques to gain biological insights into disease or to develop clinically relevant biomarkers for disease management.
© 2011 The Authors. Respirology © 2011 Asian Pacific Society of Respirology.

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Year:  2011        PMID: 21299687     DOI: 10.1111/j.1440-1843.2011.01942.x

Source DB:  PubMed          Journal:  Respirology        ISSN: 1323-7799            Impact factor:   6.424


  4 in total

1.  The effect of cell subset isolation method on gene expression in leukocytes.

Authors:  Nadejda Beliakova-Bethell; Marta Massanella; Cory White; Steven Lada; Pinyi Du; Florin Vaida; Julià Blanco; Celsa A Spina; Christopher H Woelk
Journal:  Cytometry A       Date:  2013-09-20       Impact factor: 4.355

Review 2.  Strategic applications of gene expression: from drug discovery/development to bedside.

Authors:  Jane P F Bai; Alexander V Alekseyenko; Alexander Statnikov; I-Ming Wang; Peggy H Wong
Journal:  AAPS J       Date:  2013-01-15       Impact factor: 3.603

3.  Atlas of RNA sequencing profiles for normal human tissues.

Authors:  Maria Suntsova; Nurshat Gaifullin; Daria Allina; Alexey Reshetun; Xinmin Li; Larisa Mendeleeva; Vadim Surin; Anna Sergeeva; Pavel Spirin; Vladimir Prassolov; Alexander Morgan; Andrew Garazha; Maxim Sorokin; Anton Buzdin
Journal:  Sci Data       Date:  2019-04-23       Impact factor: 6.444

4.  Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases.

Authors:  Arsen Arakelyan; Lilit Nersisyan; Martin Petrek; Henry Löffler-Wirth; Hans Binder
Journal:  Front Genet       Date:  2016-05-06       Impact factor: 4.599

  4 in total

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