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An Integrated Approach for Microprotein Identification and Sequence Analysis
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Large-Scale Sequence Comparison.

Devi Lal1, Mansi Verma2

  • 1Ramjas College, University of Delhi, New Delhi, 110 007, India.

Methods in Molecular Biology (Clifton, N.J.)
|November 30, 2016
PubMed
Summary
This summary is machine-generated.

Sequence comparison is crucial for categorizing millions of DNA and protein sequences in genomic databases. This chapter reviews essential methods like sequence alignment, PAM and BLOSUM matrices, and tools such as BLAST, FASTA, and genome comparison software.

Keywords:
Accepted point mutationBLOcks SUbstitution MatrixConservative substitutionsDynamic programming algorithmE valueGap penaltyGlobal and local alignmentHeuristic approachHomologyIndelsOrthologsParalogsScoring matrixSubstitutions

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Genomic databases contain millions of sequences requiring categorization by structure and function.
  • Sequence comparison is fundamental for assigning putative roles to novel DNA and protein sequences.

Purpose of the Study:

  • To provide foundational knowledge on sequence comparison techniques.
  • To review established and current methods for pairwise and large-scale genome comparison.

Main Methods:

  • Explains sequence alignment as a primary comparison method for various sequence lengths.
  • Describes the principles behind PAM and BLOSUM matrices used in sequence scoring.
  • Introduces widely used tools like BLAST and FASTA for sequence searching.

Main Results:

  • Highlights the importance of sequence comparison for functional annotation.
  • Discusses the utility of global and local alignment strategies.
  • Presents an overview of specialized genome comparison tools (e.g., LAGAN, MumMER, BLASTZ, AVID).

Conclusions:

  • Effective sequence comparison is vital for understanding genomic data.
  • A range of tools exists for diverse sequence comparison needs, from pairwise to whole-genome analysis.