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Related Experiment Video

Updated: Jun 24, 2026

Multi-locus Variable-number Tandem-repeat Analysis of the Fish-pathogenic Bacterium Yersinia ruckeri by Multiplex PCR and Capillary Electrophoresis
10:33

Multi-locus Variable-number Tandem-repeat Analysis of the Fish-pathogenic Bacterium Yersinia ruckeri by Multiplex PCR and Capillary Electrophoresis

Published on: June 17, 2019

SimMLST: simulation of multi-locus sequence typing data under a neutral model.

Xavier Didelot1, Daniel Lawson, Daniel Falush

  • 1Department of Statistics, University of Warwick, Coventry, UK. X.Didelot@warwick.ac.uk

Bioinformatics (Oxford, England)
|March 17, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces SimMLST, a new coalescent method for simulating bacterial multi-locus sequence typing (MLST) data and their evolutionary history. This tool aids in understanding bacterial population genetics and isolate characterization.

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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Related Experiment Videos

Last Updated: Jun 24, 2026

Multi-locus Variable-number Tandem-repeat Analysis of the Fish-pathogenic Bacterium Yersinia ruckeri by Multiplex PCR and Capillary Electrophoresis
10:33

Multi-locus Variable-number Tandem-repeat Analysis of the Fish-pathogenic Bacterium Yersinia ruckeri by Multiplex PCR and Capillary Electrophoresis

Published on: June 17, 2019

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Area of Science:

  • Bacteriology
  • Computational Biology
  • Population Genetics

Background:

  • Multi-locus sequence typing (MLST) is a standard method for bacterial isolate characterization.
  • MLST has been applied to over 50,000 isolates across more than 50 bacterial species.

Purpose of the Study:

  • To develop a coalescent method for jointly simulating MLST data and the underlying clonal genealogy.
  • To provide a computational tool for researchers studying bacterial evolution and population structure.

Main Methods:

  • Developed a coalescent-based simulation method.
  • Implemented the method in C++ with a Qt4 graphical user interface (GUI).
  • Made the software (SimMLST) publicly available under the GNU General Public License.

Main Results:

  • The study presents a novel method for simulating correlated MLST data and genealogical histories.
  • The SimMLST software allows for the generation of realistic synthetic MLST datasets.

Conclusions:

  • SimMLST provides a valuable tool for exploring bacterial population genetics using simulated MLST data.
  • The method facilitates a deeper understanding of the evolutionary processes shaping bacterial populations.