MPIPairwiseStatSig: parallel pairwise statistical significance estimation of local sequence alignment

No abstract is available for this paper.

• Publication year

  2010

• Venue

  IEEE International Symposium on High-Performance Parallel Distributed Computing

• Publication date

  2010-06-21

• Fields of study

  Biology, Computer Science

• Identifiers
  DOI 10.1145/1851476.1851545
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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  2009influential reference
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  2003cited by this paper
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  2002cited by this paper
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  2001influential reference
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  2001cited by this paper
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  2000influential reference
• Flexible sequence similarity searching with the FASTA3 program package.

  2000influential reference
• Rapid Assessment of Extremal Statistics for Gapped Local Alignment

  1999influential reference
• Empirical statistical estimates for sequence similarity searches.

  1998influential reference
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  1996cited by this paper
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  1996influential reference
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  1996cited by this paper
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  1994cited by this paper
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  1994cited by this paper
• Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes.

  1990influential reference
• Basic local alignment search tool.

  1990cited by this paper
• Improved tools for biological sequence comparison.

  1988cited by this paper
• Identification of common molecular subsequences.

  1981cited by this paper

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  2011cites this paper
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  2011cites this paper
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• Derived distribution points heuristic for fast pairwise statistical significance estimation

  2010cites this paper