Biological Big Data Analytics (original) (raw)

2018, A Deep Dive into NoSQL Databases: The Use Cases and Applications

Big data analytics uses efficient analytic techniques to discover hidden patterns, correlations, and other insights from big data. It brings significant cost advantages, enhances the performance of decision making, and creates new products to meet customers’ needs. This method has various applications in plants, bioinformatics, healthcare, etc. It can be improved with various techniques such as machine learning, intelligent tools, and network analysis. This chapter describes applications of big data analytics in biological systems. These applications can be conducted in systems biology by using cloud-based databases (e.g., NoSQL). The chapter explains the improvement of big data technology in plants community with machine learning. Furthermore, it presents various tools to apply big data analytics in bioinformatics systems. Medical signal and genomics are two major fields in healthcare environments that would be improved by this type of analytical method. Finally, the chapter discusses on several use cases of healthcare information system.

Emerging trend of big data analytics in bioinformatics: a literature review

Advancement of unparalleled data in bioinformatics over the years is a major concern for storage and management. Such massive data must be handled efficiently to disseminate knowledge. Computational advancements in information technology present feasible analytical solutions to process such data. In this context, the paper is an attempt to highlight the influence of big data in bioinformatics. Some of the concepts emphasised are definition of big data; architectural platforms supporting data analytics; followed by the application of above-mentioned analytical techniques towards complex problems in bioinformatics. The challenges and future prospects of big data analytics in bioinformatics are briefly discussed. This paper provides a comprehensive summary of several data analytical techniques available for bioinformatics researchers and computer scientists.

Impact of Big Data Analytics in Bioinformatics: A Literature Review

Advancement of unparalleled data in bioinformatics over the years is a major concern for storage and management. Such massive data must be handled efficiently to disseminate knowledge. Computational advancements in information technology present feasible analytical solutions to process such data. In this context, the paper is an attempt to highlight the influence of big data in bioinformatics. Some of the concepts emphasized are definition of big data; architectural platforms supporting data analytics; followed by the application of above mentioned analytical techniques towards complex problems in bioinformatics. The challenges and future prospects of big data analytics in bioinformatics are briefly discussed. This paper provides a comprehensive summary of several data analytical techniques available for bioinformatics researchers and computer scientists.

Big Data Analysis Techniques for Visualization of Genomics in Medicinal Plants

Biotechnology

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.

BIG DATA IN BIOSCIENCES

Increasingly bigger and complex data sets are generated within biosciences. To gain useful and actionable knowledge from them it is necessary that these are processed using the efficient " Big Data " approaches. This article provides an overview of the Big Data concept and its applications in biosciences.

Big Data: A Challenging Opportunity for Biomedical Informatics

Amity Journal of Computational Sciences (AJCS) , 2019

In the current technological world big data technologies are being used in bio-informatics research and healthcare. The huge amount of clinical data have been generated and collected at an unoccupied speed and scale. For example, the number of sequencing technologies in the new era producing the trillions of DNA sequence data per day, and the different applications of EHRs-Electronic health records are specifying huge amount of patient data. The amount of processing and analyzing healthcare data is about to decrease dramatically with the help of available technologies. The Big data applications provide new opportunities to enhance new knowledge and establish different type methods to improve the quality of existing healthcare system. The objective of the paper is to evaluate the applications of analytics of Big Data in the biomedicine and healthcare field and the associated outcomes.

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