Towards scaling elementary flux mode computation

Ehsan Ullah*, Mona Yosafshahi, Soha Hassoun

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

While elementary flux mode (EFM) analysis is now recognized as a cornerstone computational technique for cellular pathway analysis and engineering, EFM application to genome-scale models remains computationally prohibitive. This article provides a review of aspects of EFM computation that elucidates bottlenecks in scaling EFM computation. First, algorithms for computing EFMs are reviewed. Next, the impact of redundant constraints, sensitivity to constraint ordering and network compression are evaluated. Then, the advantages and limitations of recent parallelization and GPU-based efforts are highlighted. The article then reviews alternative pathway analysis approaches that aim to reduce the EFM solution space. Despite advances in EFM computation, our review concludes that continued scaling of EFM computation is necessary to apply EFM to genome-scale models. Further, our review concludes that pathway analysis methods that target specific pathway properties can provide powerful alternatives to EFM analysis.

Original languageEnglish
Pages (from-to)1875-1885
Number of pages11
JournalBriefings in Bioinformatics
Volume21
Issue number6
DOIs
Publication statusPublished - 1 Nov 2020

Keywords

  • elementary flux mode analysis
  • elementary flux modes
  • parallel computing
  • pathway analysis
  • scalability

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