ArticleBioinformatics (Oxford, England)2020
COMER2: GPU-accelerated sensitive and specific homology searches.
Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Article
- GTalign: spatial index-driven protein structure alignment, superposition, and search.Nature communications · 2024Article
- Frequent nonhomologous replacement of replicative helicase loaders by viruses inProceedings of the National Academy of Sciences of the United States of America · 2024Article
- The COMER web server for protein analysis by homology.Bioinformatics (Oxford, England) · 2023Article
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Authors and funding
1 author.
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Abstract
summarySearching 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.
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