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Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
07:49

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Published on: August 16, 2017

Comprehensive comparison of graph based multiple protein sequence alignment strategies.

Ilya Plyusnin1, Liisa Holm

  • 1Institute of Biotechnology, University of Helsinki, P,O, Box 56, Viikinkaari 5, Helsinki, Finland. Ilja.Pljusnin@gmail.com

BMC Bioinformatics
|May 1, 2012
PubMed
Summary
This summary is machine-generated.

This study presents a novel multiple protein sequence alignment (MPSA) program, identifying optimal strategies for high-quality alignments. Pairwise alignments and single linkage clustering are key for progressive alignment, with specific methods proving most effective.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Molecular Biology

Background:

  • Multiple protein sequence alignment (MPSA) is fundamental for molecular biology applications.
  • A novel MPSA program is introduced, built on the SeqAn sequence alignment library.
  • The program features a modular structure for analyzing alignment component contributions.

Purpose of the Study:

  • To systematically compare and identify optimal strategies for multiple protein sequence alignment.
  • To evaluate the impact of different information sources, guiding trees, score transformations, and refinement options.
  • To provide a comprehensive comparison of MPSA strategies within a unified platform.

Main Methods:

  • Systematic variation of information sources, guiding trees, score transformations, and iterative refinement options.
  • Evaluation of alignment quality using BAliBASE and SABmark benchmarks.
  • Development of a modular MPSA program for flexible component analysis.

Main Results:

  • Pairwise global and local alignments provide sufficient information for high-quality MPSA.
  • Single linkage clustering is the optimal algorithm for building guiding trees in progressive alignment.
  • Triplet library extension is the most efficient consistency transformation; tree-dependent partitioning offers comparable results.

Conclusions:

  • This work provides the first comprehensive comparison of MPSA strategies using a single implementation.
  • Identifies the most effective consistency transformations and iterative refinement techniques.
  • The MPSA program is available for public use, facilitating further research.