Next-Generation Sequencing — An Overview of the History, Tools, and “Omic” Applications
By Jerzy K. Kulski. 2016
169 citations recorded by the source corpus.
Next-generation sequencing (NGS) technologies using DNA, RNA, or methylation se‐ quencing have impacted enormously on the life sciences. NGS is the choice for large-scale genomic and transcriptomic sequencing because of the high-throughput production and outputs of sequencing data in the gigabase range per instrument run and the lower cost compared to the traditional Sanger first-generation sequencing method. The vast amounts of data generated by NGS have broadened our understanding of structural and functional genomics through the concepts of “omics” ranging from basic genomics to in‐ tegrated systeomics, providing new insight into the workings and meaning of genetic conservation and diversity of living things. NGS today is more than ever about how dif‐ ferent organisms use genetic information and molecular biology to survive and repro‐ duce with and without mutations, disease, and diversity within their population networks and changing environments. In this chapter, the advances, applications, and challenges of NGS are reviewed starting with a history of first-generation sequencing fol‐ lowed by the major NGS platforms, the bioinformatics issues confronting NGS data stor‐ age and analysis, and the impacts made in the fields of genetics, biology, agriculture, and medicine in the brave, new world of ”omics.”
Subfields: Ecology, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/7c18ebbe16279689b3a4a5a5de8de88f0d330040
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Citations in the corpus
- The rise of artificial intelligence in healthcare applications (2020, background): “The current clinical system would need a redesign to be able to use such genomics data and the benefits hereof [13].”
- Artificial intelligence (AI) and big data in cancer and precision oncology (2020, methodology): “This device is capable of single-molecule sequencing minus library preparation at lower costs and reduced time without compromising quality by generating longer reads [11,14].”