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Analysis of Microarray Data using Artificial Intelligence Based Techniques

Analysis of Microarray Data using Artificial Intelligence Based Techniques

Khalid Raza
ISBN13: 9781522504276|ISBN10: 1522504273|EISBN13: 9781522504283
DOI: 10.4018/978-1-5225-0427-6.ch011
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MLA

Raza, Khalid. "Analysis of Microarray Data using Artificial Intelligence Based Techniques." Handbook of Research on Computational Intelligence Applications in Bioinformatics, edited by Sujata Dash and Bidyadhar Subudhi, IGI Global, 2016, pp. 216-239. https://doi.org/10.4018/978-1-5225-0427-6.ch011

APA

Raza, K. (2016). Analysis of Microarray Data using Artificial Intelligence Based Techniques. In S. Dash & B. Subudhi (Eds.), Handbook of Research on Computational Intelligence Applications in Bioinformatics (pp. 216-239). IGI Global. https://doi.org/10.4018/978-1-5225-0427-6.ch011

Chicago

Raza, Khalid. "Analysis of Microarray Data using Artificial Intelligence Based Techniques." In Handbook of Research on Computational Intelligence Applications in Bioinformatics, edited by Sujata Dash and Bidyadhar Subudhi, 216-239. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-5225-0427-6.ch011

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Abstract

Microarray is one of the essential technologies used by the biologists to measure genome-wide expression levels of genes in a particular organism under some particular conditions or stimuli. As microarrays technologies have become more prevalent, the challenges of analyzing these data for getting better insight about biological processes have essentially increased. Due to availability of artificial intelligence based sophisticated computational techniques, such as artificial neural networks, fuzzy logic, genetic algorithms, and many other nature-inspired algorithms, it is possible to analyse microarray gene expression data in a better way. In this chapter, we present artificial intelligence based techniques for the analysis of microarray gene expression data. Further, challenges in the field and future work direction have also been suggested.

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