Name
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. |
Year | Venue | Keywords |
|---|---|---|
2016 | BIBM | high-throughput sequencing,grid,cloud,personalised medicine |
Field | DocType | Citations |
Data science,Computer science,Genomics,Whole genome sequencing,DNA sequencing,Bioinformatics,Data management,Grid,Personalized medicine,Cloud computing | Conference | 0 |
PageRank | References | Authors |
0.34 | 17 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gaye Lightbody | 1 | 28 | 7.65 |
| Valeriia Haberland | 2 | 10 | 3.91 |
| Fiona Browne | 3 | 74 | 12.99 |
| Jaine K. Blayney | 4 | 2 | 2.08 |
| Huiru Zheng | 5 | 458 | 74.87 |