Name
Title | ||
|---|---|---|
BioBloom tools: fast, accurate and memory-efficient host species sequence screening using bloom filters. |
Abstract | ||
|---|---|---|
Large datasets can be screened for sequences from a specific organism, quickly and with low memory requirements, by a data structure that supports time-and memory-efficient set membership queries. Bloom filters offer such queries but require that false positives be controlled. We present BioBloom Tools, a Bloom filter-based sequence-screening tool that is faster than BWA, Bowtie 2 (popular alignment algorithms) and FACS (a membership query algorithm). It delivers accuracies comparable with these tools, controls false positives and has low memory requirements. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1093/bioinformatics/btu558 | BIOINFORMATICS |
Field | DocType | Volume |
Bloom filter,Data structure,Data mining,Computer science,Software,Bioinformatics,False positive paradox | Journal | 30 |
Issue | ISSN | Citations |
23 | 1367-4803 | 3 |
PageRank | References | Authors |
0.42 | 4 | 10 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Justin Chu | 1 | 11 | 4.70 |
| Sara Sadeghi | 2 | 3 | 0.42 |
| Anthony Raymond | 3 | 18 | 1.94 |
| Shaun D Jackman | 4 | 72 | 7.37 |
| Ka Ming Nip | 5 | 3 | 0.75 |
| Richard Mar | 6 | 3 | 0.42 |
| Hamid Mohamadi | 7 | 66 | 5.37 |
| Yaron S Butterfield | 8 | 3 | 0.42 |
| Gordon Robertson | 9 | 120 | 15.23 |
| Inanc Birol | 10 | 78 | 9.34 |