Applications of microarray
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Microarrays can be used for gene expression profiling, comparative genomics, disease diagnosis, drug discovery, and toxicological research. It allows researchers to examine thousands of genes simultaneously and see changes in gene expression patterns. Microarrays have applications in areas like cancer classification, pharmacogenomics, and toxicogenomics. While a powerful tool, microarrays also have limitations like being expensive to create and requiring time to develop.
Applications of microarray
- 2. Microarr ay as a gene expressi on profiling tool Microarr ays and comparat ive genomic s Disease diagnosi s Drug discover y Toxicolog ical research or toxicoge nomics
- 3. "when, where, and to what magnitude genes of interest are expressed. Measure changes in the multigene patterns of expression The arrays used in this kind of analysis are called expression chips profiling of immune responses, identification of enzyme substrates, and quantifying protein-small molecule, protein-protein and protein-DNA/RNA interactions
- 4. DNA microarrays can: 1) identify diagnostic or prognostic biomarkers; 2) classify diseases 3) monitor the response to therapy; and 4) understand the mechanisms involved in the genesis of disease processes.
- 6. comparative gene mutation analysis to analyse genomic alterations such as sequence and single nucleotide polymorphisms. In microbiology microarray gene mutation analysis is directed to characterisation of genetic differences among microbial isolates, particularly closely related species Viral-microbe interactions
- 9. Different types of cancer have been classified on the basis of the organs in which the tumors develop. Now, with the evolution of microarray technology, it will be possible for the researchers to further classify the types of cancer on the basis of the patterns of gene activity in the tumor cells Identification of gene expression profiles or “genomic fingerprints” will allow clinicians to differentiate harmless white lesions from precancerous lesions or from very early cancer
- 11. Microarray technology has extensive application in Pharmacogenomics. Comparative analysis of the genes from a diseased and a normal cell will help the identification of the biochemical constitution of the proteins synthesized by the diseased genes.
- 13. Microarray technology provides a robust platform for the research of the impact of toxins on the cells and their passing on to the progeny. Toxicogenomics establishes correlation between responses to toxicants and the changes in the genetic profiles of the cells exposed to such toxicants. The microarray permits researchers to examine thousands of different genes in the same experiment and thus to obtain a good understanding of the relative levels of expression between different genes in an organism.
- 16. Microarray is a recently developed functional genomics technology that has powerful applications in a wide array of biological medical sciences, agriculture, biotechnology and environmental studies. Since many universities research institutions and industries have established microarray based core facilities and services, microarrays have become a readily accessible, widely used technology for investigating biological systems.
- 17. Lettieri, T. (2006). Recent applications of DNA microarray technology to toxicology and ecotoxicology. Environmental health perspectives, 114(1), 4. Tarca, A. L., Romero, R., & Draghici, S. (2006). Analysis of microarray experiments of gene expression profiling. American Journal of Obstetrics & Gynecology, 195(2), 373-388. Kumar, A., Sen, A., & Das, P. (2010). Microarray based gene expression: a novel approach for identification and development of potential drug and effective vaccine against visceral Leishmaniasis. International Journal of Advances in Pharmaceutical Sciences, 1(1).
- 18. Santos, F., Martínez-García, M., Parro, V., & Antón, J. (2014). Microarray tools to unveil viral- microbe interactions in nature. Frontiers in Ecology and Evolution, 2, 31. Duarte, J. G., & Blackburn, J. M. (2017). Advances in the development of human protein microarrays. Expert review of proteomics, 14(7), 627-641. Oostlander, A. E., Meijer, G. A., & Ylstra, B. (2004). Microarray‐based comparative genomic hybridization and its applications in human genetics. Clinical genetics, 66(6), 488-495.
- 19. Gupta, S., Manubhai, K. P., Mukherjee, S., & Srivastava, S. (2017). Serum Profiling for Identification of Autoantibody Signatures in Diseases Using Protein Microarrays. Serum/Plasma Proteomics: Methods and Protocols, 303-315. Kumar, A., Sen, A., & Das, P. (2010). Microarray based gene expression: a novel approach for identification and development of potential drug and effective vaccine against visceral Leishmaniasis. International Journal of Advances in Pharmaceutical Sciences, 1(1).
Editor's Notes
- #4: Analysis of gene expression data from a microarray experiment can reveal details of the cell cycle, providing valuable data on the points at which gene mutation leads to cancerous growth, as well as opportunities of therapeutic intervention.. Expression chips could also be used to diagnose diseases, such as the identification of new genes involved in environmentally triggered diseases which affect systems such as the immune, nervous, and pulmonary or respiratory systems.
- #9: Figure 1. A summary of the application of microarray tools to the study of viral ecology. As described in the text, nucleic acids (from oligonucleotide to complete viral genomes), proteins, or glycans can be immobilized on a solid surface to probe different target molecules (nucleic acids, glycans, proteins). The interaction between immobilized probes and targets is normally detected by fluorescence although other detection systems are also available.
- #11: For example, we can compare the different patterns of gene expression levels between a group of cancer patients and a group of normal patients and identify the gene associated with that particular cancer. About 600 genes were found to be oral cancer associated. These oral cancer associated genes include oncogenes, tumor suppressors, transcription factors, xenobiotic enzymes, metastatic proteins, differentiation markers, and genes that have not been implicated in oral cancer. The database created provides a verifiable global profile of gene expression during oral carcinogenesis, revealing the potential role of known genes as well as genes that have not been previously implicated in oral cancer.