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Updated: Jun 28, 2026

Peptide-based Identification of Functional Motifs and their Binding Partners
14:28

Peptide-based Identification of Functional Motifs and their Binding Partners

Published on: June 30, 2013

Proteome analysis based on motif statistics.

P Nicodème1, T Doerks, M Vingron

  • 1Laboratory Statistics and Genomes, CNRS - Génopole Evry, F EMBL-Heidelberg, Germany. nicodeme@genopole.cnrs.fr

Bioinformatics (Oxford, England)
|October 19, 2002
PubMed
Summary
This summary is machine-generated.

Statistical analysis of protein motifs in genomes reveals functional importance. Over- or under-representation of motifs suggests systematic, functionally significant occurrences, impacting protein databank annotations.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Amino acid motifs in databases like Prosite may occur by chance.
  • Assessing motif significance requires mathematical evaluation of occurrence frequency.
  • Understanding motif occurrence is crucial for protein fold and function determination.

Purpose of the Study:

  • To investigate the statistical over- or under-representation of motifs in complete proteomes.
  • To differentiate between chance and functionally significant motif occurrences.
  • To explore the implications for protein databank annotations.

Main Methods:

  • Utilized mathematical advances for assessing motif significance.
  • Analyzed the over- or under-representation of 266 Prosite motifs across 42 proteomes.
  • Employed statistical methods to evaluate motif occurrences within complete genomes.

Main Results:

  • Demonstrated that statistical over- or under-representation of motifs indicates functional importance.
  • Identified motif occurrences as either chance or systematic and functionally significant.
  • Highlighted the impact of these findings on databank annotations.

Conclusions:

  • Statistical analysis of motif representation in proteomes provides functional insights.
  • Systematic motif occurrences suggest functional relevance within an organism.
  • This approach enhances the accuracy and utility of protein databank information.