Name
Abstract | ||
|---|---|---|
High-throughput genetic sequencing produces the ultimate \"big data\": a human genome sequence contains more than 3B base pairs, and more and more characteristics, or annotations, are being recorded at the base-pair level. Locating areas of interest within the genome is a challenge for researchers, limiting their investigations. We describe our vision of adapting \"big data\" ranked search to the problem of searching the genome. Our goal is to make searching for data as easy for scientists as searching the Internet. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2795218.2795221 | ExploreDB@SIGMOD/PODS |
Field | DocType | Citations |
Data science,Genome,Data mining,Data exploration,Information retrieval,Ranking,Computer science,DNA sequencing,Human genome,Big data,Limiting,The Internet | Conference | 2 |
PageRank | References | Authors |
0.67 | 5 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| V. M. Megler | 1 | 41 | 5.16 |
| David Maier | 2 | 5639 | 1666.90 |
| Daniel Bottomly | 3 | 15 | 2.94 |
| Libbey White | 4 | 2 | 0.67 |
| Shannon K. McWeeney | 5 | 2 | 1.01 |
| Beth Wilmot | 6 | 2 | 0.67 |