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Role of Data Mining Techniques in Bioinformatics

Role of Data Mining Techniques in Bioinformatics
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Author(s): Pushpa Singh (KIET Group of Institutions, Delhi-NCR, Ghaziabad, India)and Narendra Singh (G. L. Bajaj Insitute of Management and Research, India)
Copyright: 2024
Pages: 12
Source title: Research Anthology on Bioinformatics, Genomics, and Computational Biology
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/979-8-3693-3026-5.ch063

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Abstract

Data mining offers a highly effective technique that is useful in research and development of bioinformatics. Bioinformatics consists biological information such as DNA, RNA, and protein. Data mining tasks/techniques are classification, prediction, clustering, association, outlier detection, regression, and pattern tracking. Data mining provides important correlation, hidden patterns, and knowledge from the bioinformatics data set. This paper presents the role of data mining techniques in bioinformatics application. Classification of gene and protein structure, analyzing the gene expression, association of co-disease, outlier detection and gene selection, protein structure prediction, and drug discovery are some typical biological example that has proven data mining as a suitable technique for bioinformatics.

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