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Related Experiment Videos

Analysing isoenzyme band patterns using similarity coefficients: a personal computer program.

J R Stevens1, R E Cibulskis

  • 1Tsetse Research Laboratory, University of Bristol, U.K.

Computer Methods and Programs in Biomedicine
|December 1, 1990
PubMed
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This study introduces a Fortran 77 program for analyzing trypanosome isoenzyme patterns, aiding in understanding biochemical relationships. The software is versatile, applicable to various data types like DNA fingerprints for broader epidemiological research.

Area of Science:

  • Bioinformatics
  • Parasitology
  • Molecular Biology

Background:

  • African trypanosomiasis, or sleeping sickness, is a significant public health concern.
  • Understanding the genetic diversity and relationships of Trypanosoma parasites is crucial for disease control.
  • Existing methods for analyzing parasite isoenzyme patterns can be limiting.

Purpose of the Study:

  • To develop a versatile computer program for analyzing isoenzyme patterns of trypanosomes.
  • To facilitate the elucidation of biochemical relationships between trypanosome populations from diverse hosts and geographic regions.
  • To provide a tool applicable to various data types, including DNA fingerprints.

Main Methods:

  • Development of a Fortran 77 computer program.

Related Experiment Videos

  • Input of isoenzyme band patterns from ASCII files.
  • Calculation of similarity coefficients using four distinct measures suitable for presence/absence data.
  • Output of a similarity matrix compatible with ordination methods and dendrogram/icicle plot generation.

    • Main Results:

    • A functional computer program capable of analyzing isoenzyme data was created.
    • The program accommodates diverse data sources, including DNA fingerprints.
    • The generated similarity matrix supports advanced analytical techniques like principal coordinates analysis.

    Conclusions:

    • The developed program offers a flexible and powerful tool for analyzing trypanosome isoenzyme and molecular data.
    • It enables robust biochemical and epidemiological investigations of parasite populations.
    • The software's adaptability extends its utility beyond trypanosomiasis research.