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Rapid multiple protein sequence search by parallel and heterogeneous computation
論文作者 Li, JF; Wang, ZY; Fan, XW; Yao, RJ; Zhang, GQ; Fan, R; Wang, ZF
期刊/會(huì)議名稱(chēng) BIOINFORMATICS
論文年度 2024
論文類(lèi)別
摘要

Motivation Protein sequence database search and multiple sequence alignment generation is a fundamental task in many bioinformatics analyses. As the data volume of sequences continues to grow rapidly, there is an increasing need for efficient and scalable multiple sequence query algorithms for super-large databases without expensive time and computational costs.Results We introduce Chorus, a novel protein sequence query system that leverages parallel model and heterogeneous computation architecture to enable users to query thousands of protein sequences concurrently against large protein databases on a desktop workstation. Chorus achieves over 100x speedup over BLASTP without sacrificing sensitivity. We demonstrate the utility of Chorus through a case study of analyzing a similar to 1.5-TB large-scale metagenomic datasets for novel CRISPR-Cas protein discovery within 30 min.Availability and implementation Chorus is open-source and its code repository is available at https://github.com/Bio-Acc/Chorus.

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