Big Data Analysis Techniques for Visualization of Genomics in Medicinal Plants

Big Data Analysis Techniques for Visualization of Genomics in Medicinal Plants

Hithesh Kumar (Siddaganga Institute of Technology, India), Vivek Chandramohan (Siddaganga Institute of Technology, India), Smrithy M. Simon (Siddaganga Institute of Technology, India), Rahul Yadav (Siddaganga Institute of Technology, India) and Shashi Kumar (GenEclat Technologies, India)
Copyright: © 2019 |Pages: 34
DOI: 10.4018/978-1-5225-8903-7.ch032

Abstract

In this chapter, the complete overview and application of Big Data analysis in the field of health care industries, Clinical Informatics, Personalized Medicine and Bioinformatics is provided. The major tools and databases used for the Big Data analysis are discussed in this chapter. The development of sequencing machines has led to the fast and effective ways of generating DNA, RNA, Whole Genome data, Transcriptomics data, etc. available in our hands in just a matter of hours. The complete Next Generation Sequencing (NGS) huge data analysis work flow for the medicinal plants are discussed in the chapter. This chapter serves as an introduction to the big data analysis in Next Generation Sequencing and concludes with a summary of the topics of the remaining chapters of this book.
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Background

What Is Big Data?

When a large set of datasets becomes too complex or difficult to deal, such types of data are usually termed as Big Data. The challenges related with this field are Capture, Curation, Storage, Search, Sharing, Transfer, Analysis and Visualization of the data. Traditional systems like RDBMS (Relational Database Management Systems) failed to handle Big Data. In order to get meaningful information, to interconnect the different pieces of various types of data and to get value from Big Data, new technologies and tools were developed (Jacobs, 2009).

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