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Related Experiment Videos

'Multifrequency' location and clustering of sequence patterns from proteins.

E Ollivier1, H Soldano, A Viari

  • 1ABI, Institut Curie Section Physique-Chemie et CTIS, Centre de recherche INRA, Paris, France.

Computer Applications in the Biosciences : CABIOS
|January 1, 1991
PubMed
Summary

This study introduces advanced signal-processing techniques to identify protein sequence patterns by analyzing multiple (code frequency) pairs simultaneously. These multifrequency methods enhance pattern detection and visualization for biological sequence analysis.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Sequence Analysis

Background:

  • Previous work established a signal-processing method to derive (code frequency) pairs from protein families.
  • This method allowed for individual analysis of pairs to locate and extract sequence patterns.

Purpose of the Study:

  • To extend the existing signal-processing method for detecting and visualizing patterns using multiple (code frequency) pairs concurrently.
  • To introduce and describe two novel 'multifrequency' approaches.

Main Methods:

  • Developed two multifrequency methods: one using sequence rewriting with summarized frequency symbols, and another employing pattern clustering for associated pairs.
  • Applied these methods to analyze protein families, including calcium-binding proteins and serine proteases.

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Main Results:

  • Successfully extended the signal-processing approach to handle multiple (code frequency) pairs simultaneously.
  • Both multifrequency methods effectively defined significant consensus sequences.
  • Demonstrated the utility of the methods with specific protein families.

Conclusions:

  • The proposed multifrequency methods offer an improved way to detect and visualize complex sequence patterns in protein families.
  • These techniques advance the analysis of protein sequences by considering multiple characteristic pairs concurrently.