Literature DB >> 11208413

DNA microarray technology and application.

M Bednár1.   

Abstract

DNA microarrays (collections of DNA probes arranged on a shared base) have recently enlarged the spectrum of commercially available laboratory-ready kits in molecular biology. They are powerful new tools for the investigation of global changes in gene expression profiles in cells and tissues. Their assembly process is automatized and the DNA microarrays are further miniaturized. The DNA microarrays are used in search for various specific genes (e.g. connected with an infectious agent) or in gene polymorphism and expression analysis. They will be widely used to investigate expression of various genes connected with various diseases in order to find causes of these diseases and to enable their accurate treatment. Since the DNA microarray assembly technology has been based on methods widely used in the semiconductor industry, we can expect a rapid onset of the routine use of this revolutionary device.

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Year:  2000        PMID: 11208413

Source DB:  PubMed          Journal:  Med Sci Monit        ISSN: 1234-1010


  9 in total

1.  A glance at DNA microarray technology and applications.

Authors:  Amir Ata Saei; Yadollah Omidi
Journal:  Bioimpacts       Date:  2011-08-04

2.  Single oligoarray-based detection of specific M918T mutation in RET oncogene in multiple endocrine neoplasia type 2B.

Authors:  R A Pacheco-Rivera; E Hernández-Zamora; B González-Yebra; K Beattie; R Maldonado-Rodríguez; J C Santiago-Hernández; M E Medrano-Ortiz de Zárate; M Salcedo
Journal:  Clin Exp Med       Date:  2011-01-21       Impact factor: 3.984

3.  Gene expression changes in areas of focal loss of retinal ganglion cells in the retina of DBA/2J mice.

Authors:  Lampros Panagis; Xiujun Zhao; Yongchao Ge; Lizhen Ren; Thomas W Mittag; John Danias
Journal:  Invest Ophthalmol Vis Sci       Date:  2009-09-08       Impact factor: 4.799

Review 4.  OMICS Applications for Medicinal Plants in Gastrointestinal Cancers: Current Advancements and Future Perspectives.

Authors:  Rongchen Dai; Mengfan Liu; Xincheng Xiang; Yang Li; Zhichao Xi; Hongxi Xu
Journal:  Front Pharmacol       Date:  2022-02-04       Impact factor: 5.810

5.  Revealing Potential Diagnostic Gene Biomarkers Associated with Immune Infiltration in Patients with Renal Fibrosis Based on Machine Learning Analysis.

Authors:  Yu-Chao Sun; Zhen-Zhen Qiu; Fu-Li Wen; Jin-Quan Yin; Hao Zhou
Journal:  J Immunol Res       Date:  2022-04-20       Impact factor: 4.493

6.  Identification of the Diagnostic Biomarker VIPR1 in Hepatocellular Carcinoma Based on Machine Learning Algorithm.

Authors:  Song Ge; Chen-Rui Xu; Yan-Ming Li; Yu-Lin Zhang; Na Li; Fei-Tong Wang; Liang Ding; Jian Niu
Journal:  J Oncol       Date:  2022-09-15       Impact factor: 4.501

7.  Machine Learning and Novel Biomarkers Associated with Immune Infiltration for the Diagnosis of Esophageal Squamous Cell Carcinoma.

Authors:  Jipeng Zhang; Nian Zhang; Xin Yang; Xiangbin Xin; Cheng-Hui Jia; Sen Li; Qiang Lu; Tao Jiang; Tao Wang
Journal:  J Oncol       Date:  2022-08-30       Impact factor: 4.501

8.  Regulatory network rewiring for secondary metabolism in Arabidopsis thaliana under various conditions.

Authors:  Qi Lv; Rong Cheng; Tieliu Shi
Journal:  BMC Plant Biol       Date:  2014-07-04       Impact factor: 4.215

9.  Optical Genome Mapping in Routine Human Genetic Diagnostics-Its Advantages and Limitations.

Authors:  Paul Dremsek; Thomas Schwarz; Beatrix Weil; Alina Malashka; Franco Laccone; Jürgen Neesen
Journal:  Genes (Basel)       Date:  2021-12-08       Impact factor: 4.096

  9 in total

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