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Related Experiment Video

Updated: Feb 9, 2026

Production and Optimization of LTE, a Leishmania tarentolae Derived Cell-Free Protein Expression System for Recombinant Protein Production
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Recco: recombination analysis using cost optimization.

Jochen Maydt1, Thomas Lengauer

  • 1Max-Planck Institut für Informatik Saarbrücken, Germany. jmaydt@mpi-inf.mpg.de

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|February 21, 2006
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Summary
This summary is machine-generated.

Recco is a new, fast method for detecting recombination in pathogen evolution. It accurately identifies recombinant sequences and breakpoints, outperforming existing tools like Geneconv in key scenarios.

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Area of Science:

  • Evolutionary Biology
  • Bioinformatics
  • Genetics

Background:

  • Recombination is a key driver in the evolution of pathogens like HIV and malaria.
  • Current methods for detecting and analyzing recombination are insufficient, necessitating new approaches.

Purpose of the Study:

  • To introduce Recco, a novel and efficient method for detecting sequence recombination.
  • To provide a tool for analyzing recombinant sequences and identifying breakpoints.

Main Methods:

  • Recco scores the cost of generating a sequence via mutation and recombination from others in a multiple sequence alignment.
  • A visualization tool aids in locating recombination breakpoints.
  • Analysis involves varying a parameter (alpha) that weights recombination against mutation costs.

Main Results:

  • Recco is comparable to Geneconv on random genealogies but significantly outperforms it in relevant recombination scenarios.
  • The cost curve analysis provides insights into identifying recombinant sequences.

Conclusions:

  • Recco offers a powerful and efficient new method for recombination detection.
  • The tool aids in understanding pathogen evolution and sequence analysis.