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Related Experiment Videos

Score distributions for simultaneous matching to multiple motifs

T L Bailey1, M Gribskov

  • 1San Diego Supercomputer Center, California 92186-9784, USA. tbailey@sdsc.edu

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|April 1, 1997
PubMed
Summary

This study introduces a novel method for protein sequence database searches using multiple motifs, enhancing sensitivity and specificity. The approach combines individual motif scores to provide a more accurate overall p-value for identifying homologous protein families.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Protein sequence analysis relies on identifying conserved motifs to understand protein families.
  • Existing methods for discovering multiple motifs can be used for database similarity searches.
  • Simultaneously using multiple motifs can improve the accuracy of these searches.

Purpose of the Study:

  • To develop and validate a method for protein sequence database similarity searches using multiple motifs.
  • To improve the sensitivity and specificity of database searches compared to single-motif approaches.
  • To accurately estimate the statistical significance (p-value) of search results.

Main Methods:

  • Utilizing multiple weight matrices representing protein families for database searches.

Related Experiment Videos

  • Defining a p-value based on a target sequence's score against all motifs.
  • Employing a Gumbel distribution approximation for combined motif scores.
  • Calculating a "reduced variate" from motif scores and using their sum as a test statistic.

    • Main Results:

    • Estimating single motif score distributions with Gaussian extreme value distribution is insufficient.
    • Re-estimating Gaussian parameters from observed scores corrects p-value estimation accuracy.
    • The sum of reduced variates approximates the distribution of the test statistic well.
    • Combined multiple motif p-values yield significantly better database search results than single motifs.

    Conclusions:

    • The developed method accurately estimates p-values for multiple motif-based protein sequence similarity searches.
    • Combining multiple motifs significantly enhances the sensitivity and specificity of database searches.
    • This approach offers a more reliable way to identify homologous protein families in large databases.