Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius 10257, Lithuania.
Bioinformatics. 2020 Jun 1;36(11):3570-3572. doi: 10.1093/bioinformatics/btaa185.
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.
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.
mindaugas.margelevicius@bti.vu.lt.
Supplementary data are available at Bioinformatics online.
在海量的序列数据中搜索同源性特别注重速度。我们提出了一种完全重写的基于蛋白质序列轮廓比对的敏感同源性搜索方法 COMER2，它能够在轻量级笔记本电脑上搜索大型数据库。通过利用 CUDA 功能的图形处理单元的强大功能，它比 HHsearch 快 20 倍，HHsearch 是一种使用现代 CPU 上的矢量化指令的最先进的方法。
COMER2 是跨平台的开源软件，可在 https://sourceforge.net/projects/comer2 和 https://github.com/minmarg/comer2 上获得。它可以轻松地从源代码或使用独立安装程序进行安装。
mindaugas.margelevicius@bti.vu.lt。
补充数据可在 Bioinformatics 在线获得。
