Paper review: An overview on microarray technologies
DOI:
https://doi.org/10.12928/bamme.v1i1.3854Keywords:
affymetrix, bioinformatics, gene expression, Illumina, microarray technologyAbstract
Bioinformatics is a branch in Statistics which is still unpopular among statistics students in Indonesia. Bioinformatics research used microarray technology, because data is available through to microarray experiment on tissue sample at hand. Microarray technology has been widely used to provide data for bioinformatics research, since it was first introduced in late 1990, particularly in life sciences and biotechnology research. The emergence and development of the Covid-19 disease further reinforces the need to understand bioinformatics and its technology. There are two of the most advance platforms in microarray technology, namely, are the Affymetrix GeneChip and Illumina BeadArray. This paper aims to give an overview about microarray technology on the two platforms and the advantage of using them on bioinformatics research.References
Amaratunga, A., & Cabrera, J. (2004). Exploration and analysis of DNA microarray and protein array data. New Jersey: John Wiley & Sons.
Bakers, S. C. (2013). Next-generation sequencing vs. microarrays: Is it time to switch?. Genetic Engineering & Biotechnology News. Retrieved March 4th, 2021 from http://www.genengnews.com/gen-articles/next-generation-sequencing-vs-microarrays/4689/.
Barnes, M., Freudenberg, J., Thompson, S., Aronow, B., & Pavlidis, P. (2005). Experimental comparison and cross-validation of the Affymetrix and Illumina gene expression analysis platforms. Nucleic Acids Research, 33(18), 5914-5923.
Bartlett, A., Penders, B., & Lewis, J. (2017). Bioinformatics: indispensable, yet hidden in plain sight?. BMC Bioinformatics, 18(1), 1-4.
Belmawa. (2019). Decree of Director General of Students and Learning Affairs of the Indonesian Ministry of Research Technology and Higher Education Number 46/B/HK/2019 about the list of department in higher education. Jakarta: Ministry of Research Technology and Higher Education.
Burgoine, K. (n.d.). Origins of G-Quadruplex DNA. Retrieved February 22th, 2021 from https://www.ch.ic.ac.uk/local/projects/burgoine/origins.txt.html.
Draghici, S. (2003). Data analysis tools for DNA microarrays. Florida: Chapman & Hall.
Fajriyah, R. (2014). Microarray data analysis: Background correction and differentially expressed genes. Dissertation. Styria: TU Graz.
Fajriyah, R. (2015). Generalized beta convolution model of the true intensity for the Illumina BeadArrays, Thailand Statistician, 13(2), 145-167.
Fajriyah, R. (2016). A study of convolution models for background correction of BeadArrays, Austrian Journal of Statistics, 45(2), 15-33.
Fan, J. B., Hu, S. X., Craumer, W. C., & Barker, D. L. (2005). BeadArrayâDÌŒcÌ-based solutions for enabling the promise of pharmacogenomics. BioTechniques, 39, 583-588.
Fan, J. B., Gunderson, K. L., Bibikova, M., Yeakley, J. M., Chen, J., Garcia, E. W., Lebruska, L. L., Laurent, M., Shen, R., & Barker, D. (2006). Illumina universal bead arrays. Methods in Enzymology, 410, 57-73.
Gabig, M., & Wegrzyn, G. (2001). An introduction to DNA Chips: principles, technology, applications and analysis. Acta Biochimica Polonica, 48(3), 615-622.
Grigoryev, Y. (2011). How DNA microarrays are built. Retrieved February 22nd, 2021 from https://bitesizebio.com/7463/how-dna-microarrays-are-built/.
Hoheisel, J. D. (2006). Microarray technology: beyond transcript profiling and genotype analysis. Nature, 7, 200-210.
Horizny, C. (2019). The drug discovery process. Retrieved February 22nd, 2021 from https://www.taconic.com/taconic-insights/quality/drug-development-process.html.
Lansdowne, L. E. (2020). Exploring the drug development process. Retrieved February 22nd, 2021 from https://www.technologynetworks.com/drug-discovery/articles/exploring-the-drug-development-process-331894.
Lee, M. L. (2006). Analysis of microarray gene expression data. New York: Springer.
McLachlan, G. J., Do, K. A., & Ambroise, C. (2004). Analyzing microarray gene expression data. New Jersey: John Wiley & Sons.
Mohs, R. C., & Greig, N. H. (2017). Drug discovery and development: Role of basic biological research. Alzheimer's & Dementia: Translational Research & Clinical Interventions, 3(4), 651-657. doi: 10.1016/j.trci.2017.10.005.
Oliphant, A., Barker, D. L., Stuelpnagel, J. R., & Chee, M. S. (2002). BeadArray technology: Enabling an accurate, cost-effective approach to high-throughput genotyping. BioTechniques, 32, S56-S61.
Peae A. C., Solas, D., Sullivan, E. J., Cronin, M. T., Holmes, C. P., & Fodor, S. A. (1994). Light-generated oligonu- cleotide arrays for rapid DNA sequence analysis. Proceeding National Academy of Sciences, 91, 5022-5026.
Sartor, M. A., Medvedovic, M., & Aronow, B. J. (2003). Microarray data normalization: The art and science of overcoming technical variance to maximize the detection of biologic variance. In E. Blalock (Ed.), A Beginner’s Guide to Microarrays. Massachusetts: Kluwer Academy Publishers.
Steemers, F. J., & Gunderson, K. L. (2005). Pharmacogenomics, 6, 777 - 782.
Zhang, A. (2006). Advanced analysis of gene expression microarray data. Singapore: World Scientific Publishing.
Bakers, S. C. (2013). Next-generation sequencing vs. microarrays: Is it time to switch?. Genetic Engineering & Biotechnology News. Retrieved March 4th, 2021 from http://www.genengnews.com/gen-articles/next-generation-sequencing-vs-microarrays/4689/.
Barnes, M., Freudenberg, J., Thompson, S., Aronow, B., & Pavlidis, P. (2005). Experimental comparison and cross-validation of the Affymetrix and Illumina gene expression analysis platforms. Nucleic Acids Research, 33(18), 5914-5923.
Bartlett, A., Penders, B., & Lewis, J. (2017). Bioinformatics: indispensable, yet hidden in plain sight?. BMC Bioinformatics, 18(1), 1-4.
Belmawa. (2019). Decree of Director General of Students and Learning Affairs of the Indonesian Ministry of Research Technology and Higher Education Number 46/B/HK/2019 about the list of department in higher education. Jakarta: Ministry of Research Technology and Higher Education.
Burgoine, K. (n.d.). Origins of G-Quadruplex DNA. Retrieved February 22th, 2021 from https://www.ch.ic.ac.uk/local/projects/burgoine/origins.txt.html.
Draghici, S. (2003). Data analysis tools for DNA microarrays. Florida: Chapman & Hall.
Fajriyah, R. (2014). Microarray data analysis: Background correction and differentially expressed genes. Dissertation. Styria: TU Graz.
Fajriyah, R. (2015). Generalized beta convolution model of the true intensity for the Illumina BeadArrays, Thailand Statistician, 13(2), 145-167.
Fajriyah, R. (2016). A study of convolution models for background correction of BeadArrays, Austrian Journal of Statistics, 45(2), 15-33.
Fan, J. B., Hu, S. X., Craumer, W. C., & Barker, D. L. (2005). BeadArrayâDÌŒcÌ-based solutions for enabling the promise of pharmacogenomics. BioTechniques, 39, 583-588.
Fan, J. B., Gunderson, K. L., Bibikova, M., Yeakley, J. M., Chen, J., Garcia, E. W., Lebruska, L. L., Laurent, M., Shen, R., & Barker, D. (2006). Illumina universal bead arrays. Methods in Enzymology, 410, 57-73.
Gabig, M., & Wegrzyn, G. (2001). An introduction to DNA Chips: principles, technology, applications and analysis. Acta Biochimica Polonica, 48(3), 615-622.
Grigoryev, Y. (2011). How DNA microarrays are built. Retrieved February 22nd, 2021 from https://bitesizebio.com/7463/how-dna-microarrays-are-built/.
Hoheisel, J. D. (2006). Microarray technology: beyond transcript profiling and genotype analysis. Nature, 7, 200-210.
Horizny, C. (2019). The drug discovery process. Retrieved February 22nd, 2021 from https://www.taconic.com/taconic-insights/quality/drug-development-process.html.
Lansdowne, L. E. (2020). Exploring the drug development process. Retrieved February 22nd, 2021 from https://www.technologynetworks.com/drug-discovery/articles/exploring-the-drug-development-process-331894.
Lee, M. L. (2006). Analysis of microarray gene expression data. New York: Springer.
McLachlan, G. J., Do, K. A., & Ambroise, C. (2004). Analyzing microarray gene expression data. New Jersey: John Wiley & Sons.
Mohs, R. C., & Greig, N. H. (2017). Drug discovery and development: Role of basic biological research. Alzheimer's & Dementia: Translational Research & Clinical Interventions, 3(4), 651-657. doi: 10.1016/j.trci.2017.10.005.
Oliphant, A., Barker, D. L., Stuelpnagel, J. R., & Chee, M. S. (2002). BeadArray technology: Enabling an accurate, cost-effective approach to high-throughput genotyping. BioTechniques, 32, S56-S61.
Peae A. C., Solas, D., Sullivan, E. J., Cronin, M. T., Holmes, C. P., & Fodor, S. A. (1994). Light-generated oligonu- cleotide arrays for rapid DNA sequence analysis. Proceeding National Academy of Sciences, 91, 5022-5026.
Sartor, M. A., Medvedovic, M., & Aronow, B. J. (2003). Microarray data normalization: The art and science of overcoming technical variance to maximize the detection of biologic variance. In E. Blalock (Ed.), A Beginner’s Guide to Microarrays. Massachusetts: Kluwer Academy Publishers.
Steemers, F. J., & Gunderson, K. L. (2005). Pharmacogenomics, 6, 777 - 782.
Zhang, A. (2006). Advanced analysis of gene expression microarray data. Singapore: World Scientific Publishing.
Downloads
Published
2021-03-24
Issue
Section
Articles
License
Copyright (c) 2021 Rohmatul Fajriyah
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
