======================================================== CRANBERRY: Chemical ReAction Network numBERs summaRY ======================================================== GNU Octave (https://www.gnu.org/software/octave/index) was used to develop the functions used here. ========= Functions ========= The function network_numbers returns the values of the following network numbers of a chemical reaction network: - Species (m) - Complexes (n) - Reactant complexes (n_r) - Reversible reactions (r_rev) - Irreversible reactions (r_irrev) - Reactions (r) = r_irrev + 2 r_rev - Linkage classes (l) - Strong linkage classes (sl) - Terminal linkage classes (t) - Rank (s) - Reactant rank (q) - Deficiency (delta) = n - l - s - Reactant deficiency (delta_p) = n_r - q The output variable 'model' allows the user to view the complete network with all the species listed in the 'species' field of the structure 'model'. network_numbers uses the following functions: 1. init_graph - OUTPUT: Creates an empty structure that represents an undirected graph. The structure has the following fields: 'vertices' and 'edges'. - INPUT: none 2. add_vertex - OUTPUT: Adds a vertex to an undirected graph. This is indicated in the 'vertices' field of the structure representing the graph. - INPUTS: - g: a structure with fields 'vertices' and 'edges' - v: a string representing the vertex 3. add_edge - OUTPUT: Adds an undirected edge between two vertices. The vertex connected to a vertex is indicated in the subfield 'vertex' and the label for the edge is in the subfield 'label'. Both subfields are under the field 'edges' corresponding to the vertex. The field and subfields belong to the structure representing the graph. - INPUTS: - g: a structure with fields 'vertices' and 'edges' - v1, v2: strings representing the vertices connected by an undirected edge (make sure 'add_vertex' has been used to add the vertices 'v1' and 'v2' to g) 4. add_path - OUTPUT: Adds a directed edge between two vertices. The vertex connected to a vertex is indicated in the subfield 'vertex' and the label for the edge is in the subfield 'label'. Both subfields are under the field 'edges' corresponding to the vertex. The field and subfields belong to the structure representing the graph. - INPUTS: - g: a structure with fields 'vertices' and 'edges' - v1, v2: strings representing the vertices connected by a directed edge (make sure 'add_vertex' has been used to add the vertices 'v1' and 'v2' to g) Parts of the code come from the file model_analysis.m which is part of the ERNEST toolbox for chemical chemical reaction network theory [3]. The toolbox can be downloaded from https://www.sissa.it/fa/altafini/papers/SoAl09/. The codes for the computation for the number of reversible reaction, irreversible reactions, reactions, reactant rank, and reactant deficiency are unique from the author. Discussions on reactant rank and reactant deficiency can be found on [2]. ================================= How to fill out 'model' structure ================================= 'model' is the input for the function network_numbers. It is a structure, representing the CRN, with the following fields: - id: name of the model - species: a list of all species in the network; this is left blank since incorporated into the function is a step which compiles all species used in the model - reaction: a list of all reactions in the network, each with the following subfields: - id: a string representing the reaction - reactant: has the following further subfields: - species: a list of strings representing the species in the reactant complex - stoichiometry: a list of integers representing the stoichiometry of each species in the reactant complex (listed in the same order of the species) - product: has the following further subfields: - species: a list of strings representing the species in the product complex - stoichiometry: a list of integers representing the stoichiometry of each species in the product complex (listed in the same order of the species) - reversible: has the value 'true' or 'false' indicating if the reaction is reversible or not, respectively ======== Examples ======== 2 examples are included in this folder, all based on [1]: - Example 1: ARL3-S Molecular network of Leishmaniasis infectious disease - Example 2: ECJ3-G Yeast trehalose system =================== Contact Information =================== For questions, comments, and suggestions, feel free to contact me at pvnlubenia@yahoo.co.uk. - Patrick Lubenia (19 June 2022) ========== References ========== [1] Arceo C, Jose E, Lao A, Mendoza E (2016) Reaction networks and kinetics of biochemical systems (supplementary materials). Math Biosci 283:13-29. https://doi.org/10.1016/j.mbs.2016.10.004 [2] Arceo C, Jose E, Lao A, Mendoza E (2017) Reactant subspaces and kinetics of chemical reaction networks. J Math Chem 56:395Ð422. http://doi.org/10.1007/s10910-017-0809-x [3] Soranzo N, Altafini C (2009) ERNEST: a toolbox for chemical reaction network theory. Bioinform 25(21):2853Ð2854. https://doi.org/10.1093/bioinformatics/btp513