Functional alignment of metabolic networks

Arnon Mazza*, Allon Wagner, Eytan Ruppin, Roded Sharan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Network alignment has become a standard tool in comparative biology, allowing the inference of protein function, interaction and orthology. However, current alignment techniques are based on topological properties of networks and do not take into account their functional implications. Here we propose, for the first time, an algorithm to align two metabolic networks by taking advantage of their coupled metabolic models. These models allow us to assess the functional implications of genes or reactions, captured by the metabolic fluxes that are altered following their deletion from the network. Such implications may spread far beyond the region of the network where the gene or reaction lies. We apply our algorithm to align metabolic networks from various organisms, ranging from bacteria to humans, showing that our alignment can reveal functional orthology relations that are missed by conventional topological alignments.

Original languageEnglish
Title of host publicationResearch in Computational Molecular Biology - 19th Annual International Conference, RECOMB 2015, Proceedings
EditorsTeresa M. Przytycka
PublisherSpringer Verlag
Number of pages13
ISBN (Electronic)9783319167053
StatePublished - 2015
Event19th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2015 - Warsaw, Poland
Duration: 12 Apr 201515 Apr 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference19th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2015


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