Big Data and Hadoop in Biology: Introduction, Implementation and Applications

The materializing high-throughput technologies in 21st Century have contributed to the aggregate of data produced by mankind to increase each year. The consequent "Big-Data" in biology, particularly contributed by next- generation sequencing technologies, may accelerate our understanding of human disease biology, thereby significantly changing our present way of practicing medicine. However, the plethora of opportunities, suggested by the extent of genome sequencing, besides its ensuing inexpensive nature, combined with its applications in the clinical background is marred by challenges. The main issues plaguing the application of Big Data comprise the limitations of storage, data processing, data management and analytics challenge, because of which much of this data remains under-utilized and under-interpreted. Hadoop is a Java-based data processing and analytics technology is cutting edge in the domain of computer science in the Big Data space. In the proposed work, we intend to include the applications of Hadoop in the different fields of biology such as biomedicine, genomics, healthcare and bioinformatics, and different Hadoop-based tools which may be used to solve biology based problems.