Literature DB >> 12942629

[Differential gene expression analysis by DNA microarrays technology and its application in molecular oncology].

A E Frolov1, A K Godwin, O O Favorova.   

Abstract

Accumulation of genetic and epigenetic aberrations leads to malignant transformation of normal cells. Functional studies of cancer using genomic and proteomic tools will help to reveal the true complexity of the processes leading to cancer development in humans. Until recently, diagnosis and prognosis of cancer was based on conventional pathologic criteria and epidemiological evidence. Certain tumors were divided only into relatively broad histological and morphological subcategories. Rapidly developing methods of differential gene expression analysis promote the search for clinically relevant genes changing their expression levels during malignant transformation. DNA microarrays offer a unique possibility to rapidly assess the global expression picture of thousands genes in any given time point and compare the detailed combinatory analysis results of global expression profiles for normal and malignant cells at various functional stages or separate experimental conditions. Acquisition of such "genetic portraits" allows searching for regularity and difference in expression patterns of certain genes, understanding their function and pathological importance, and ultimately developing the "molecular nosology" of cancer. This review describes the basis of DNA microarray technology and methodology, and focuses on their applications in molecular classification of tumors, drug sensitivity and resistance studies, and identification of biological markers of cancer.

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Year:  2003        PMID: 12942629

Source DB:  PubMed          Journal:  Mol Biol (Mosk)        ISSN: 0026-8984


  4 in total

1.  Transferring genomics to the clinic: distinguishing Burkitt and diffuse large B cell lymphomas.

Authors:  Chulin Sha; Sharon Barrans; Matthew A Care; David Cunningham; Reuben M Tooze; Andrew Jack; David R Westhead
Journal:  Genome Med       Date:  2015-07-01       Impact factor: 11.117

2.  Quantitative RT-PCR analysis of differentially expressed genes in Quercus suber in response to Phytophthora cinnamomi infection.

Authors:  Ghazal Ebadzad; Alfredo Cravador
Journal:  Springerplus       Date:  2014-10-17

3.  Network-based support vector machine for classification of microarray samples.

Authors:  Yanni Zhu; Xiaotong Shen; Wei Pan
Journal:  BMC Bioinformatics       Date:  2009-01-30       Impact factor: 3.169

4.  A novel approach for discovering condition-specific correlations of gene expressions within biological pathways by using cloud computing technology.

Authors:  Tzu-Hao Chang; Shih-Lin Wu; Wei-Jen Wang; Jorng-Tzong Horng; Cheng-Wei Chang
Journal:  Biomed Res Int       Date:  2014-01-22       Impact factor: 3.411

  4 in total

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