{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "***Note: this is the stoichBondGraph.ipynb notebook. The\n", "PDF version \"The stoichBondGraph module: From Stoichiometry to Bond Graph\"\n", "is available [here](stoichBondGraph.pdf).***" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Introduction\n", "The bond graph approach \n", " \n", "to modelling biomolecular systems of interest to systems biologists developed independently from the stoichiometric approach \n", ".\n", "\n", "However, the conceptual point of intersection of the two approaches is the fact that the stoichiometric matrix is the modulus of the conceptual multiport transformer linking reactions to species.\n", "This means that the two approaches are complementary and each can build on the strengths of the other.\n", "\n", "This tutorial illustrates how a stoichiometric system description can be used to automatically create the corresponding bond graph. However, more compex systems such as the ecoli core model \n", "\n", "can also be translated in the same way.\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Import some python code\n", "The bond graph analysis uses a number of Python modules:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "## Some useful imports\n", "import BondGraphTools as bgt\n", "import numpy as np\n", "\n", "## Stoichiometry to BG\n", "import stoichBondGraph as stbg" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Create a stoichiometric representation\n", "\n", "In this context a stoichimetric representation is a python dictionary with the following fields\n", "\n", "- name (string): the name of the bg to be created\n", "- N (numpy integer array): the stoichiometric matrix\n", "- species (list of strings): the names of the species\n", "- reaction (list of strings): the names of the reaction\n", "\n", "Optionally, the forward and reverse stoichometric matrices Nf and Nr can be included instead of N\n", "\n", "Note that there is one species per row, and one reaction per column, of N\n", "\n", "A file name.py is written containing the function model() which returns the bg in bgt form\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Example\n", "This example corresponds to ABCD_abg.svg in Tutorial svgBondGraph." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "## Stoichiometric matrix N\n", "N = np.array(\n", " [\n", " [-1, 0, 0, 0],\n", " [ 0,-1, 0, 0],\n", " [ 0, 0, 1, 0],\n", " [ 0, 0, 0, 1],\n", " [-1, 0, 0, 1],\n", " [ 1,-1, 0, 0],\n", " [ 0, 1,-1, 0],\n", " [ 0, 0, 1,-1]\n", " ]\n", ")\n", "\n", "## Species and reactions\n", "species = ['A', 'B', 'C', 'D', 'E1', 'E2', 'E3', 'E4']\n", "reaction = ['r1', 'r2', 'r3', 'r4']\n", "\n", "## Pack into a dict with name 'ABCDE_abg'\n", "s = {\n", " 'name':'BG_abg',\n", " 'N':N,\n", " 'species':species,\n", " 'reaction':reaction\n", " }\n", "\n", "## Convert to a bondgraph\n", "stbg.model(s)\n", "\n", "## And import\n", "import BG_abg\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Draw the BG" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "## Draw the BG\n", "bgt.draw(BG_abg.model())" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.8" } }, "nbformat": 4, "nbformat_minor": 2 }