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An evolutionary approach for searching metabolic pathways.

Matias F Gerard1, Georgina Stegmayer, Diego H Milone

  • 1Center for Research and Development of Information Systems (CIDISI), National Scientific and Technical Research Council (CONICET), Argentina; Research Center for Signals, Systems and Computational Intelligence (Sinc(i)), FICH-UNL, National Scientific and Technical Research Council (CONICET), Argentina.

Computers in Biology and Medicine
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Summary

This study introduces an evolutionary algorithm to find metabolic pathways connecting compounds, improving bioinformatics searches. Its performance is compared against traditional methods.

Keywords:
Evolutionary algorithmsMetabolic pathwaysSearch strategies

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Identifying metabolic pathways is crucial for understanding compound relationships, particularly in data mining applications.
  • Existing search strategies for metabolic pathways can be computationally intensive.

Purpose of the Study:

  • To propose and evaluate a novel evolutionary algorithm for efficiently searching metabolic pathways between two compounds.
  • To analyze the impact of mutation rate on the evolutionary algorithm's performance.

Main Methods:

  • Development of a custom evolutionary algorithm with specific operators and a fitness function.
  • Comparison of the proposed algorithm against two classical search strategies.
  • Analysis of mutation rate effects on pathway search.

Main Results:

  • The evolutionary algorithm demonstrates effective pathway searching capabilities.
  • Performance metrics indicate the algorithm's viability compared to classical approaches.
  • Mutation rate significantly influences the search process.

Conclusions:

  • The proposed evolutionary algorithm offers a promising approach for metabolic pathway discovery.
  • Further research can optimize algorithm parameters for enhanced performance.
  • The developed algorithm and dataset are publicly available for research use.