Systematic exploration of an efficient amino acid substitution matrix: MIQS

Kentaro Tomii, Kazunori Yamada

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)


Amino acid sequence comparisons to find similarities between proteins are fundamental sequence information analyses for inferring protein structure and function. In this study, we improve amino acid substitution matrices to identify distantly related proteins. We systematically sampled and benchmarked substitution matrices generated from the principal component analysis (PCA) subspace based on a set of typical existing matrices. Based on the benchmark results, we identified a region of highly sensitive matrices in the PCA subspace using kernel density estimation (KDE). Using the PCA subspace, we were able to deduce a novel sensitive matrix, called MIQS, which shows better detection performance for detecting distantly related proteins than those of existing matrices. This approach to derive an efficient amino acid substitution matrix might influence many fields of protein sequence analysis. MIQS is available at

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Number of pages13
Publication statusPublished - 2016 Aug 1

Publication series

NameMethods in Molecular Biology
ISSN (Print)1064-3745


  • Amino acid substitution matrix
  • Pairwise alignment
  • Protein sequence comparison
  • Remote homology detection

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics


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