A genome-scale metabolic network alignment method within a hypergraph-based framework using a rotational tensor-vector product.

ABSTRACT: Biological network alignment aims to discover important similarities and differences and thus find a mapping between topological and/or functional components of different biological molecular networks. Then, the mapped components can be considered to correspond to both their places in the network topology and their biological attributes. Development and evolution of biological network alignment methods has been accelerated by the rapidly increasing availability of such biological networks, yielding a repertoire of tens of methods based upon graph theory. However, most biological processes, especially the metabolic reactions, are more sophisticated than simple pairwise interactions and contain three or more participating components. Such multi-lateral relations are not captured by graphs, a

SUBMITTER: Shen T 

PROVIDER: S-EPMC6219566 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature