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The challenge of constructing, classifying, and representing metabolic pathways.

Ron Caspi1, Kate Dreher, Peter D Karp

  • 1Bioinformatics Research Group, SRI International, Menlo Park, CA 94025, USA. ron.caspi@sri.com

FEMS Microbiology Letters
|June 11, 2013
PubMed
Summary

MetaCyc curators organize metabolic pathway data for accessibility and use in pathway prediction software. This review details challenges and rules for classifying metabolic pathways to enhance data utility.

Keywords:
MetaCycmetabolic databasemetabolic pathwaypathway prediction

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Area of Science:

  • Metabolic pathway curation and bioinformatics.

Background:

  • Centralized access to metabolic information is crucial for scientists, educators, and students.
  • The MetaCyc database provides metabolic data in a pathway-based framework.
  • MetaCyc serves as a template for pathway prediction software, generating databases for numerous organisms.

Purpose of the Study:

  • To describe the challenges faced by MetaCyc curators in defining pathway boundaries and classification.
  • To outline the criteria and rules developed for representing and classifying metabolic pathway information.
  • To discuss the impact of these curation decisions on pathway prediction in new species.

Main Methods:

  • Review of curation criteria and decision-making processes for metabolic pathway representation in MetaCyc.
  • Analysis of pathway classification within a broader pathway ontology.
  • Discussion of the functional consequences of curation choices on pathway prediction software.

Main Results:

  • Identification of key challenges in standardizing metabolic pathway definitions and classifications.
  • Development of specific rules and criteria by MetaCyc curators for consistent data representation.
  • Understanding the impact of these rules on the accuracy and utility of automated pathway prediction.

Conclusions:

  • Standardized representation and classification of metabolic pathways are essential for database utility and prediction software.
  • The MetaCyc curation process addresses challenges to maximize the value of metabolic information.
  • Decisions in pathway representation directly influence the effectiveness of predicting metabolic pathways in novel organisms.