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Reconstructing High-Quality Large-Scale Metabolic Models with merlin.

Oscar Dias1, Miguel Rocha2, Eugénio Campos Ferreira2

  • 1Centre of Biological Engineering, University of Minho, Braga, Portugal. odias@ceb.uminho.pt.

Methods in Molecular Biology (Clifton, N.J.)
|December 10, 2017
PubMed
Summary

This tutorial introduces merlin, a tool for reconstructing genome-scale metabolic models. It guides users through model assembly and curation using genomic data, aiding in metabolic network analysis.

Keywords:
Genome functional annotationGenome-scale metabolic modelsTransport proteins annotationmerlin

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Area of Science:

  • Metabolic Engineering
  • Computational Biology
  • Systems Biology

Background:

  • Genome-scale metabolic models (GEMs) are crucial for understanding cellular metabolism.
  • Reconstructing accurate GEMs from genomic data is a complex and time-consuming process.
  • Existing tools often lack comprehensive features for annotation, assembly, and curation.

Purpose of the Study:

  • To describe the basic principles and features of the merlin software for reconstructing GEMs.
  • To provide a detailed tutorial on using merlin for model assembly and curation.
  • To demonstrate the integration of genomic annotation with metabolic model construction.

Main Methods:

  • Utilizing merlin's two main modules for genome annotation and model assembly.
  • Employing merlin's tools for curating reactions, gene rules, and biomass precursors (e.g., e-protein, e-DNA, e-RNA).
  • Integrating sequenced genome data as the starting point for model reconstruction.

Main Results:

  • merlin facilitates the assembly of GEMs by integrating genomic annotation.
  • The tool provides specific functionalities for model curation, including reaction gene rules and biomass placeholders.
  • The process allows for the assessment of experimental data for model validation.

Conclusions:

  • merlin offers a comprehensive workflow for reconstructing and curating genome-scale metabolic models.
  • The software streamlines the process from genomic data to a validated metabolic model.
  • This approach aids researchers in building accurate and useful metabolic models for various biological studies.