Affiliation:
1. Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius 10257, Lithuania
Abstract
Abstract
Summary
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 graphics processing units, 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.
Contact
mindaugas.margelevicius@bti.vu.lt
Supplementary information
Supplementary data are available at Bioinformatics online.
Funder
European Regional Development Fund
Research Council of Lithuania
LMTLT
Publisher
Oxford University Press (OUP)
Subject
Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability
Cited by
9 articles.
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