Name
Abstract | ||
|---|---|---|
Genome analysis fundamentally starts with a process known as read mapping, where sequenced fragments of an organism's genome are compared against a reference genome. Read mapping is currently a major bottleneck in the entire genome analysis pipeline, because state-of-the-art genome sequencing technologies are able to sequence a genome much faster than the computational techniques employed to analyze the genome. We describe the ongoing journey in significantly improving the performance of read mapping. We explain state-of-the-art algorithmic methods and hardware-based acceleration approaches. Algorithmic approaches exploit the structure of the genome as well as the structure of the underlying hardware. Hardware-based acceleration approaches exploit specialized microarchitectures or various execution paradigms (e.g., processing inside or near memory). We conclude with the challenges of adopting these hardware-accelerated read mappers. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/MM.2020.3013728 | IEEE Micro |
Keywords | DocType | Volume |
ongoing journey,read mapping,sequenced fragments,organism,reference genome,entire genome analysis pipeline,state-of-the-art genome sequencing technologies,state-of-the-art algorithmic methods,hardware-based acceleration approaches,hardware-accelerated read mappers | Journal | 40 |
Issue | ISSN | Citations |
5 | 0272-1732 | 11 |
PageRank | References | Authors |
0.46 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammed Alser | 1 | 17 | 3.19 |
| Zülal Bingöl | 2 | 19 | 1.54 |
| Damla Senol Cali | 3 | 34 | 3.32 |
| Jeremie Kim | 4 | 263 | 13.68 |
| Saugata Ghose | 5 | 718 | 36.45 |
| Can Alkan | 6 | 312 | 26.92 |
| Onur Mutlu | 7 | 9446 | 357.40 |