TY - GEN
T1 - Functional alignment of metabolic networks
AU - Mazza, Arnon
AU - Wagner, Allon
AU - Ruppin, Eytan
AU - Sharan, Roded
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84926380763&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-16706-0_24
DO - 10.1007/978-3-319-16706-0_24
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AN - SCOPUS:84926380763
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 243
EP - 255
BT - Research in Computational Molecular Biology - 19th Annual International Conference, RECOMB 2015, Proceedings
A2 - Przytycka, Teresa M.
PB - Springer Verlag
T2 - 19th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2015
Y2 - 12 April 2015 through 15 April 2015
ER -