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A generalized global alignment algorithm.

Xiaoqiu Huang1, Kun-Mao Chao

  • 1Department of Computer Science, Iowa State University, 226 Atanasoff Hall, Ames, IA 50011-1040, USA. xqhuang@cs.iastate.edu

Bioinformatics (Oxford, England)
|January 23, 2003
PubMed
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A new algorithm, GAP3 (Global Alignment Program Version 3), identifies homologous sequences with intermittent similarities. This tool enhances sequence comparison for DNA and proteins, improving detection of distantly related sequences.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Homologous sequences can exhibit regional variations in similarity.
  • Low global similarity often results from extensive non-similar regions within homologous sequences.

Purpose of the Study:

  • To introduce a generalized global alignment algorithm and model for comparing sequences with intermittent similarities.
  • To develop a computational tool (GAP3) for analyzing such sequences.

Main Methods:

  • Developed a generalized global alignment model for sequences with ordered similar and different regions.
  • Designed a dynamic programming algorithm for optimal alignment computation.
  • Implemented the algorithm as the GAP3 computer program.

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Main Results:

  • The GAP3 program computes optimal general alignments efficiently (time proportional to sequence length product, space proportional to sum of lengths).
  • Experimental validation on DNA and protein sequences demonstrated the model's effectiveness.
  • GAP3 enhances the capability of standard alignment tools to detect homologous sequences with lower similarity.

Conclusions:

  • The generalized global alignment model and GAP3 program effectively handle sequences with intermittent similarities.
  • GAP3 extends the utility of sequence alignment for identifying distantly related homologous sequences.
  • The GAP3 program is available for academic use.