BioinformaticsBioinformaticsPeer-reviewed journal article
SWORD - a highly efficient protein database search
Abstract
MotivationProtein database search is one of the fundamental problems in bioinformatics. For decades, it has been explored and solved using different exact and heuristic approaches. However, exponential growth of data in size in recent years has brought significant challenges in improving already existing algorithms. BLASTP has been the most successful tool for protein database search, but is also becoming a bottleneck in many applications. Due to that, many different approaches have been developed to comple-ment or replace BLASTP. In this paper, we present SWORD, an efficient protein database search implementation that runs 3-4 faster than BLASTP in the sensitive mode and up to 18 faster in the fast and less accurate mode and also provides guaranteed optimal alignments for candidate sequences. SWORD is designed to be used in nearly all database search environments, but is especially suitable for large databases. Its sensitivity exceeds that of BLASTP for majority of input datasets.\n\nAvailabilitySword is freely available for download from https://github.com/rvaser/sword\n\nContactrobert.vaser@fer.hr, mile.sikic@fer.hr
- assay: protein sequence
- research focus: database / resource
- research focus: benchmarking
- approach: deep learning
- approach: statistical model
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