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Identification of metabolic pathways using pathfinding approaches: a systematic review.

Zeyad Abd Algfoor1, Mohd Shahrizal Sunar1, Afnizanfaizal Abdullah2,3,4

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Computational analysis of microbial metabolic pathways aids understanding of cellular metabolism. This review details stoichiometric and pathfinding approaches for analyzing these complex biological networks.

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Area of Science:

  • Computational biology
  • Metabolic engineering
  • Genomics

Background:

  • Metabolic pathway data for microorganisms is rapidly expanding.
  • Computational tools, especially mathematical pathfinding methods, are crucial for analyzing this data.
  • Understanding cellular metabolism computationally is vital for various biological applications.

Purpose of the Study:

  • To provide a comprehensive understanding of computational analysis for metabolic pathways in genomics.
  • To discuss stoichiometric and pathfinding approaches in metabolic pathway analysis.
  • To elaborate on different study types and evaluation metrics for pathway analysis.

Main Methods:

  • Review of stoichiometric identification models.
  • Analysis of pathway-based graph structures.
  • Exploration of pathfinding approaches in cellular metabolism.
  • Evaluation using mathematical benchmarking metrics.

Main Results:

  • Detailed elaboration of three major study types: stoichiometric models, graph analysis, and pathfinding.
  • Discussion on the application and evaluation of these computational methods.
  • Insights into the comprehension of cellular metabolism through computed pathfinding.

Conclusions:

  • Computational pathfinding approaches offer significant insights into cellular metabolism.
  • This review facilitates a better understanding of metabolic pathway analysis in genomics.
  • The discussed methods and metrics aid in evaluating pathway outcomes effectively.