FogLight: an efficient matrix-based approach to construct metabolic pathways by search space reduction

Mehrshad Khosraviani, Morteza Saheb Zamani (Corresponding Author), Gholamreza Bidkhori (Corresponding Author)

Research output: Contribution to journalArticleScientificpeer-review

6 Citations (Scopus)

Abstract

Motivation: A fundamental computational problem in the area of metabolic engineering is finding metabolic pathways between a pair of source and target metabolites efficiently. We present an approach, namely FogLight, for searching metabolic networks utilizing Boolean (AND-OR) operations represented in matrix notation to efficiently reduce the search space. This enables the enumeration of all pathways between metabolites that are too distant for the application of brute-force methods. Results: Benchmarking tests run with FogLight show that it can reduce the search space by up to 98%, after which the accelerated search for high accurate results is guaranteed. Using FogLight, several pathways between eight given pairs of metabolites are found of which the pathways from CO2 to ethanol are specifically discussed. Additionally, in comparison with three path-finding tools, namely PHT, FMM and RouteSearch, FogLight can find shorter and more pathways for attempted source-target metabolite pairs.
Original languageEnglish
Pages (from-to)398-408
JournalBioinformatics
Volume32
Issue number3
DOIs
Publication statusPublished - 2015
MoE publication typeA1 Journal article-refereed

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Keywords

  • FogLight

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