| Title |
COMER2: GPU-accelerated sensitive and specific homology searches |
| Authors |
Margelevičius, Mindaugas |
| DOI |
10.1093/bioinformatics/btaa185 |
| Full Text |
|
| Is Part of |
Bioinformatics.. Oxford : Oxford university press. 2020, vol. 36, iss. 11, p. 3570-3572.. ISSN 1367-4803. eISSN 1460-2059 |
| Keywords [eng] |
COMER2 ; homology search ; sequence alignment |
| Abstract [eng] |
Searching for homology in the vast amount of sequence data has a particular emphasis on its speed. We present a completely rewritten version of the sensitive homology search method COMER based on alignment of protein sequence profiles, which is capable of searching big databases even on a lightweight laptop. By harnessing the power of CUDA-enabled GPUs, it is up to 20 times faster than HHsearch, a state-of-the-art method using vectorized instructions on modern CPUs. AVAILABILITY AND IMPLEMENTATION: COMER2 is cross-platform open-source software available at https://sourceforge.net/projects/comer2 and https://github.com/minmarg/comer2. It can be easily installed from source code or using stand-alone installers. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
| Published |
Oxford : Oxford university press |
| Type |
Journal article |
| Language |
English |
| Publication date |
2020 |
| CC license |
|
