Cited by 22,074Genomics and Phylogenetic StudiesAlgorithms and Data CompressionFractal and DNA sequence analysis

BLAST+: architecture and applications

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Camacho, Christiam, Coulouris, George, Avagyan, Vahram, Ma, Ning, Papadopoulos, Jason, Bealer, Kevin, Madden, Thomas L·2009·BMC Bioinformatics

Abstract

Background: Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. Results: We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. Conclusion: The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.

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Research works printed but not linked: 8

  1. NCBI C toolkit http://www.ncbi.nlm.nih.gov/IEB/ToolBox/SDKDOCS/INDEX.HTML
  2. NCBI BLAST web site http://blast.ncbi.nlm.nih.gov/Blast.cgi
  3. NCBI C++ toolkit documentation http://www.ncbi.nlm.nih.gov/bookshelf/br.fcgi?book=toolkit
  4. Implementing a BlastSeqSrc http://www.ncbi.nlm.nih.gov/IEB/ToolBox/CPP_DOC/doxyhtml/_impl_blast_seqsrc_howto.html
  5. BLAST+ Command Line Applications User Manual http://www.ncbi.nlm.nih.gov/bookshelf/br.fcgi?book=helpblast
  6. Reference assembly for Human genome build 36.1 http://www.ncbi.nlm.nih.gov/genome/guide/human/release_notes.html#b36
  7. NCBI SRA Software Development Kit http://www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?cmd=show&f=software&m=software&s=software
  8. PUBLIC DOMAIN NOTICE for NCBI http://www.ncbi.nlm.nih.gov/bookshelf/br.fcgi?book=toolkit&part=toolkit.fm#A3

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Authors
Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., & Madden, T. L.
Affiliations
National Institutes of Health (US)
Corresponding author
Madden, Thomas L
Venue
BMC Bioinformatics
Published
2009-12
Volume
10
Issue
1
Pages
421-421
ISSN
1471-2105 (ISSN-L)
OpenAlex
W2142678478
Cited by
22,074
References
15
Citations by year
2026: 2652 · 2025: 2909 · 2024: 2584 · 2023: 2213 · 2022: 2114 · 2021: 2164 · 2020: 1780 · 2019: 1400 · 2018: 1093 · 2017: 979 · 2016: 725 · 2015: 518 · 2014: 412 · 2013: 241 · 2012: 144
FWCI
36.21
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • BMC Bioinformatics (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • National Institutes of Health
  • U.S. National Library of Medicine
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Physical Sciences › Computer Science › Artificial Intelligence › Algorithms and Data Compression
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
Keywords
BLAST, sequence similarity searching, chunking, command-line tool, software performance optimization, user interface
MeSH terms
Software, Sequence Alignment, Computational Biology, Databases, Genetic

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