The Role of High Performance, Grid and Cloud Computing in High-Throughput Sequencing

Gaye Lightbody, Fiona Browne, Huiru Zheng, Valeriia Haberland, Jaine Blayney

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)
22 Downloads (Pure)

Abstract

We have reached the era of full genome sequencing using high throughput sequencing technologies pouring out gigabases of reads in a day. To fully benefit from such a profusion of data high performance tools and systems are needed to extract the information lying within the sequences. This paper provides an overview of the evolution of high-throughput sequencing and the tools, infrastructure and data management developing in this space to support a key area in personalized medicine. The paper concludes by providing an outlook in the future of such technologies and their applications and how they might shape clinical governance.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherIEEE
Pages890-895
Number of pages6
ISBN (Print)978-1-5090-1611-2
DOIs
Publication statusPublished - 19 Jan 2017
EventThe Proceedings of the 2016 IEEE International Conference on Bioinformatics and Biomedicine: The 3rd Workshop on High Performance Computing on Bioinformatics (HPCB 2016) - Shenzhen, China
Duration: 19 Jan 2017 → …

Workshop

WorkshopThe Proceedings of the 2016 IEEE International Conference on Bioinformatics and Biomedicine: The 3rd Workshop on High Performance Computing on Bioinformatics (HPCB 2016)
Period19/01/17 → …

Keywords

  • high-throughput sequencing
  • grid
  • cloud
  • personalised medicine

Fingerprint Dive into the research topics of 'The Role of High Performance, Grid and Cloud Computing in High-Throughput Sequencing'. Together they form a unique fingerprint.

  • Cite this

    Lightbody, G., Browne, F., Zheng, H., Haberland, V., & Blayney, J. (2017). The Role of High Performance, Grid and Cloud Computing in High-Throughput Sequencing. In Unknown Host Publication (pp. 890-895). IEEE. https://doi.org/10.1109/BIBM.2016.7822643