Biotech Today: An International Journal of Biological Sciences
  • Year: 2017
  • Volume: 7
  • Issue: 2

Knowledge Advancement in Next Generation Sequencing Technologies and Analytics

1Agricultural Knowledge Management Unit (AKMU), ICAR-Indian Agricultural Research Institute, New Delhi-10012, India

2ADG(EP&HS), ICAR, New Delhi

*Corresponding Author Email: mishrapallavi58@gmail.com

Online published on 10 April, 2019.

Abstract

The recent shift of modern biologists towards bioinformatics services supports cultural and conceptual changes provides remarkable technology development. Especially nextgeneration sequencing has accelerated multiple areas of integrated research. Next-generation sequencing (NGS) is possibly the most dynamic and rapidly growing area of modern biology. The aims for the technology will be to lower the cost of the equipment and biochemicals involved, increasing simultaneously the reproducibility, reliability and simplicity of the techniques and protocols in operation of different omics research. During the last few years there is rapid development in sequencing technology, innovative biological applications and softwares. The growing stage of NGS technology facilitates generation of massive raw data which needs to be examined to get meaningful results. Since the introduction of NGS technology, have seen a major transformation in the way scientists extract genetic information from biological systems, revealing limitless insight about the genome. This ability has catalyzed a number of important breakthroughs, advancing scientific fields from human disease research to evolutionary science. As a result new software tools for NGS data analysis are often released as years passed away and the cost of sequencing continues to fall and the scope of sequencing projects expands to larger studies with integration into new areas. NGS is enabled by sophisticated and novel bioinformatics tools specifically created. Not only has new software been developed for a wide range of novel applications and types of data analysis, but new algorithms have also been developed for old problems and to cope with the huge volumes of data generated on new sequencing machines. The transition from the first human genome sequences to the personal genomes and genomic medicine has been made possible only because of the advances in sequencing technologies over the past 13 years.

Keywords

Bioinformatics, Next-generation Sequencing, Omics, Technologies