Connectivity matrix method for analyses of biological networks and its application to atom-level analysis of a model network of carbohydrate metabolism

An approach for analysis of biological networks is proposed. In this approach, named the connectivity matrix (CM) method, all the connectivities of interest are expressed in a matrix. Then, a variety of analyses are performed on GNU Octave or Matlab. Each node in the network is expressed as a row vector or numeral that carries information defining or characterising the node itself. Information about connectivity itself is also expressed as a row vector or numeral. Thus, connection of node n₁ to node n₂ through edge e is expressed as [n₁, n₂, e], a row vector formed by the combination of three row vectors or numerals, where n₁, n₂, and e indicate two different nodes and one connectivity, respectively. All the connectivities in any given network are expressed as a matrix, CM, each row of which corresponds to one connectivity. Using this CM method, inter-metabolite atom-level connectivity is investigated in a model metabolic network composed of the reactions for glycolysis, oxidative decarboxylation of pyruvate, citric acid cycle, pentose phosphate pathway and gluconeogenesis.