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Sequence Similarity Searching.

Gang Hu1, Lukasz Kurgan2

  • 1School of Mathematical Sciences and LPMC, Nankai University, Tianjin, China.

Current Protocols in Protein Science
|August 14, 2018
PubMed
Summary
This summary is machine-generated.

Sequence similarity searching is crucial for analyzing biological data. This guide covers BLAST tools for sequence alignment, database searching, and recent advancements like MMseqs2.

Keywords:
BLASTBLASTNBLASTPMMseqs2PSSMalignmentsequence similarity searching

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Sequence similarity searching is integral to molecular biology, aiding in the analysis of vast sequence datasets.
  • It is used to infer function, structure, and evolutionary relationships from unannotated sequences.

Purpose of the Study:

  • To introduce and explain the widely-used BLAST family of sequence similarity search tools.
  • To guide users on performing sequence similarity searches using web-based and standalone BLAST+ tools.
  • To highlight recent advancements in the field, including the MMseqs2 method.

Main Methods:

  • Explanation of core concepts in sequence alignment.
  • Demonstration of database searching using BLASTP, PSI-BLAST, and BLASTN web interfaces.
  • Description of the standalone BLAST+ software, including input, parameters, and output.

Main Results:

  • Comprehensive overview of BLAST tool functionalities for sequence similarity searching.
  • Practical guidance on utilizing various BLAST versions for biological data analysis.
  • Introduction to MMseqs2 as a fast alternative for sequence similarity searching.

Conclusions:

  • BLAST tools are essential for modern molecular biology research.
  • Understanding BLAST parameters and outputs is key for accurate sequence analysis.
  • Emerging tools like MMseqs2 offer enhanced speed and efficiency for large-scale sequence comparisons.