netgraph_split_metabolites.m

％The Metabolic Networks Toolbox contains functions to create, ％modify, display, and simulate bioche

function  graphics_object = netgraph_split_metabolites(graphics_object,met_list);

gridsize = 0.01; % distance between discrete x values
k1 = 0.1;  % overall repulsion strength
k2 = 0.01; % overall repulsion scale
k3 = 0.5;  % neighbour attraction strength
k4 = 0.1;  % neighbour attraction scale

for it = 1:length(met_list)
  metabolite = met_list{it};
  met_index  = find(strcmp(graphics_object.metnames,metabolite));
  other_indices = setdiff(1:length(graphics_object.metnames),met_index);
  actions    = find(graphics_object.N(met_index,:));
  n_new      = length(actions);
  graphics_object.metvalues  = [graphics_object.metvalues(other_indices); graphics_object.metvalues(met_index)*ones(n_new,1)];
  graphics_object.metnames   = [graphics_object.metnames(other_indices); repmat(graphics_object.metnames(met_index),n_new,1)];
  dummi = zeros(length(actions),size(graphics_object.N,2));
  for it = 1:length(actions), dummi(it, actions(it)) = graphics_object.N(met_index,actions(it)); end
  graphics_object.N = [graphics_object.N(other_indices,:); dummi];
  graphics_object.metabolite_mapping=[graphics_object.metabolite_mapping(other_indices); repmat(graphics_object.metabolite_mapping(met_index),n_new,1)];
end
  m = [zeros(length(graphics_object.metnames)) graphics_object.N; graphics_object.N' zeros(length(graphics_object.actnames))];
  m = (m~=0);
  m = m-diag(diag(m));
  db = graph_shortest_path(m,4,0);
  db(find(~isfinite(db)))=5; 
  graphics_object.m  = m;
  graphics_object.db = db;
  graphics_object.x = netgraph_find_x(graphics_object,gridsize,k1,k2,k3,k4);