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Statistical and Machine Learning Approaches for Network Analysis by Subhash C. Basak, Matthias Dehmer

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3.4 Bipartite Relationship: A Case Study of Metabolite Distribution

In the previous sections, we have focused on simple (unipartite) networks consisting of one type of nodes and edges between its nodes. For instance, in the metabolic networks mentioned in the above section, the nodes are metabolites and the edges are drawn between these nodes (i.e., between the metabolites). However, we sometimes observe biological systems represented as bipartite networks.

An interesting example of this is metabolite distributions (or species–metabolite networks), which indicate how metabolites are distributed among species (i.e., the relationship between species and metabolites). Living organisms produce various types of compounds via their metabolisms, which are believed to adaptively shape-shift with changing environment over a long evolutionary history. Thus, metabolite distributions are important in order to elucidate the design principles of metabolisms such as adaptive mechanisms.

The relationship between two types of objects is represented as a bipartite network. Bipartite networks are defined as graphs having two different node sets (in this case, species and metabolites), in which edges are only drawn between one node set and the other node set (interconnectivity). Notably, there is no edge between the nodes belonging to the same node set (intraconnectivity). In the species–metabolite networks, an edge is drawn between a species node and a metabolite node when the species has the metabolite. ...

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