notebooks/01_model_curation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "57be0ba4-2b98-42fd-8364-be431403da0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from cameo import load_model\n",
    "from cameo import fba\n",
    "\n",
    "import escher\n",
    "from escher import Builder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "504d43ca-f4af-44c9-aea3-07bb2473ecea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scaling...\n",
      " A: min|aij| =  1.000e+00  max|aij| =  1.000e+00  ratio =  1.000e+00\n",
      "Problem data seem to be well scaled\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <table>\n",
       "            <tr>\n",
       "                <td><strong>Name</strong></td>\n",
       "                <td>M_iDB858</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Memory address</strong></td>\n",
       "                <td>0x07f981e98e190</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Number of metabolites</strong></td>\n",
       "                <td>1003</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Number of reactions</strong></td>\n",
       "                <td>1330</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Number of groups</strong></td>\n",
       "                <td>84</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Objective expression</strong></td>\n",
       "                <td>1.0*biomass1.12 - 1.0*biomass1.12_reverse_e00c6</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Compartments</strong></td>\n",
       "                <td>Cytoplasm</td>\n",
       "            </tr>\n",
       "          </table>"
      ],
      "text/plain": [
       "<Model M_iDB858 at 0x7f981e98e190>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load Chromobacterium model\n",
    "model = load_model('../data/iDB858_edited.xml')\n",
    "model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8158b85-3238-497a-9bca-efd2c774b980",
   "metadata": {},
   "source": [
    "Number of metabolites: **1003**  \n",
    "Number of reactions: **1330**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "51b2e0df-3cbb-4153-9aad-48b6764bd04d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2515998481207547"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# simulasi model\n",
    "s = fba(model)\n",
    "flux = s.fluxes.to_frame()\n",
    "s.objective_value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d8e08a1d-3004-4593-bc4d-841f5e9f40b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5f05191969d44eb8876b74e28e653e02",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Builder(reaction_data={'rxn12008_c': 0.00233685938934557, 'rxn00541_c': 0.0, 'rxn00225_c': 0.0, 'rxn01674_c': …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# map from author\n",
    "builder_scratch = Builder(\n",
    "    map_json = '../data/from_team/cv_Core metabolism_MAP.json',\n",
    "    model = model,\n",
    "    reaction_data = s.fluxes\n",
    ")\n",
    "builder_scratch"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f88601f-3c80-424f-9bf7-4542f2700cb4",
   "metadata": {},
   "source": [
    "Here we can see that many reactions and metabolite does not match map id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6586276e-d210-43bb-ab88-7b941e5f9168",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let's look at map data\n",
    "import json\n",
    "with open (\"../data/from_team/cv_Core metabolism_MAP.json\", \"r\") as f:\n",
    "    data = json.loads(f.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "55ec3a57-de67-4d3e-9cbd-657fcf41997e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "reactions: 139 metabolites: 357\n"
     ]
    }
   ],
   "source": [
    "# how many reactions and metabolites in the map?\n",
    "len_reaction = len(data[1][\"reactions\"])\n",
    "len_metabolites = len([m for m in data[1][\"nodes\"] if data[1][\"nodes\"][m][\"node_type\"] == \"metabolite\"])\n",
    "print(\"reactions:\", len_reaction, \"metabolites:\", len_metabolites)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc6881fe-33c5-454e-8bd6-870dc83c7172",
   "metadata": {},
   "source": [
    "## Mapping Metabolites\n",
    "We would like to match the metabolites id with the metabolites in the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "43e04590-46d9-4a2e-8d09-4a0ca33b73bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "found 23 mismatch: ['34hpp_c', 'gln_DASH_L_c', 'glu_DASH_L_c', 'phe_DASH_L_c', 'tyr_DASH_L_c', 'phe_DASH_L_e', 'tyr_DASH_L_e', 'ser_DASH_L_c', 'trp_DASH_L_c', 'trp_DASH_L_e', '2i3ip_c', 'pdvnate_c', 'chpy_c', 'pvnate_c', 'vnate_c', 'vio_c', 'chpy_e', 'dvnate_c', 'dvio_c', 'dvio_e', 'provio_c', 'provio_e', 'vio_e']\n"
     ]
    }
   ],
   "source": [
    "# make a list of metabolites\n",
    "met_model = {m.id: m.name for m in model.metabolites}\n",
    "met_map = {data[1][\"nodes\"][m]['bigg_id']: data[1][\"nodes\"][m][\"name\"] for m in data[1][\"nodes\"] if data[1][\"nodes\"][m][\"node_type\"] == \"metabolite\"}\n",
    "\n",
    "# find mismatch\n",
    "mismatch_metabolites = [met for met in met_map.keys() if not met in met_model.keys()]\n",
    "print(f\"found {len(mismatch_metabolites)} mismatch:\", mismatch_metabolites)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3eaa30d-aa65-4bb8-b9b1-5389fa47769f",
   "metadata": {},
   "source": [
    "Not bad, only 23 mismatches in the map, let's find the correct name in the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8fa542ca-5e1c-4646-b72f-9822b6ee9b3f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "glu acgam1p_c N-Acetyl-D-glucosamine 1-phosphate\n",
      "ser achms_c O Acetyl L homoserine C6H11NO4\n",
      "glu dtdpglu_c DTDPglucose\n",
      "glu sucglu_c N2-Succinyl-L-glutamate\n",
      "glu sucgsa_c N2-Succinyl-L-glutamate 5-semialdehyde\n",
      "glu uacgam_c UDP-N-acetyl-D-glucosamine\n",
      "glu u3aga_c UDP-3-O-(3-hydroxytetradecanoyl)-N-acetylglucosamine\n",
      "tyr ibcoa_c Isobutyryl-CoA\n",
      "tyr ibcoa_c Isobutyryl-CoA\n",
      "glu hpglu_c Tetrahydropteroyltri L glutamate C24H34N8O12\n",
      "glu mhpglu_c 5 Methyltetrahydropteroyltri L glutamate C25H36N8O12\n",
      "ser hom__L_c L-Homoserine\n",
      "glu ugmd_c UDP-N-acetylmuramoyl-L-alanyl-D-gamma-glutamyl-meso-2,6-diaminopimelate\n",
      "glu ugmda_c UDP-N-acetylmuramoyl-L-alanyl-D-glutamyl-meso-2,6-diaminopimeloyl-D-alanyl-D-alanine\n",
      "glu akg_c 2-Oxoglutarate\n",
      "glu uaagmda_c Undecaprenyl-diphospho-N-acetylmuramoyl-(N-acetylglucosamine)-L-ala-D-glu-meso-2,6-diaminopimeloyl-D-ala-D-ala\n",
      "ser acser_c O-Acetyl-L-serine\n",
      "tyr butACP_c Butyryl-ACP (n-C4:0ACP)\n",
      "tyr butACP_c Butyryl-ACP (n-C4:0ACP)\n",
      "glu g6p_B_c Beta D glucose 6 phosphate C6H11O9P\n",
      "glu 6pgl_c 6-phospho-D-glucono-1,5-lactone\n",
      "tyr 3hmbcoa_c (S)-3-Hydroxy-2-methylbutyryl-CoA\n",
      "tyr 3hmbcoa_c (S)-3-Hydroxy-2-methylbutyryl-CoA\n",
      "glu ala_L_glu__L_c ala-L-glu-L\n",
      "glu forglu_c N-Formimidoyl-L-glutamate\n",
      "glu u23ga_c UDP-2,3-bis(3-hydroxytetradecanoyl)glucosamine\n",
      "tyr cpd11495_c 2-methylbutyryl-ACP\n",
      "tyr cpd11495_c 2-methylbutyryl-ACP\n",
      "ser phom_c O-Phospho-L-homoserine\n",
      "glu dtdp4d6dg_c DTDP-4-dehydro-6-deoxy-D-glucose\n",
      "glu ala_L_glu__L_e ala-L-glu-L\n",
      "phe 2h34hppr_c p-hydroxyphenylpyruvate\n",
      "phe 2h34hppr_c p-hydroxyphenylpyruvate\n",
      "glu uamag_c UDP-N-acetylmuramoyl-L-alanyl-D-glutamate\n",
      "glu uaccg_c UDP-N-acetyl-3-O-(1-carboxyvinyl)-D-glucosamine\n",
      "phe 2omph_c 2-Octaprenyl-6-methoxyphenol\n",
      "phe 2omph_c 2-Octaprenyl-6-methoxyphenol\n",
      "phe 2ohph_c 2-Octaprenyl-6-hydroxyphenol\n",
      "phe 2ohph_c 2-Octaprenyl-6-hydroxyphenol\n",
      "phe 2cpr5p_c 1-(2-Carboxyphenylamino)-1-deoxy-D-ribulose 5-phosphate\n",
      "phe 2cpr5p_c 1-(2-Carboxyphenylamino)-1-deoxy-D-ribulose 5-phosphate\n",
      "glu glc_bD_c Beta D-glucose\n",
      "glu 6pgc_c 6-Phospho-D-gluconate\n",
      "glu 2ddg6p_c 2-Dehydro-3-deoxy-D-gluconate 6-phosphate\n",
      "phe pphn_c Prephenate\n",
      "phe pphn_c Prephenate\n",
      "ser ps180_c phosphatidylserine dioctadecanoyl\n",
      "glu hmgcoa_c Hydroxymethylglutaryl CoA C27H39N7O20P3S\n",
      "glu uagmda_c Undecaprenyl-diphospho-N-acetylmuramoyl-L-alanyl-D-glutamyl-meso-2,6-diaminopimeloyl-D-alanyl-D-alanine\n",
      "ser cpd15690_c Dianteisoheptadecanoylphosphatidylserine\n",
      "glu 3mgcoa_c 3-Methylglutaconyl-CoA\n",
      "glu udpg_c UDPglucose\n",
      "ser pser__L_c O-Phospho-L-serine\n",
      "glu gly_glu__L_c gly-glu-L\n",
      "glu gly_glu__L_e gly-glu-L\n",
      "ser cpd15689_c Diisoheptadecanoylphosphatidylserine\n",
      "glu gicolipa_c glucosyl-inner core oligosaccharide lipid A\n",
      "glu acgam6p_c N-Acetyl-D-glucosamine 6-phosphate\n",
      "glu acglu_c N-Acetyl-L-glutamate\n",
      "phe 2oph_c 2-Octaprenylphenol\n",
      "phe 2oph_c 2-Octaprenylphenol\n",
      "glu acg5sa_c N-Acetyl-L-glutamate 5-semialdehyde\n",
      "glu acg5p_c N-Acetyl-L-glutamyl 5-phosphate\n",
      "glu lipidA_c 2,3,23-Tetrakis(beta-hydroxymyristoyl)-D-glucosaminyl-1,6-beta-D-glucosamine 1,4-bisphosphate\n",
      "glu acgam_e N-Acetyl-D-glucosamine\n",
      "tyr cpd04539_c 2-Amino-3-oxo-4-phosphonooxybutyrate\n",
      "tyr cpd04539_c 2-Amino-3-oxo-4-phosphonooxybutyrate\n",
      "glu u3hga_c UDP-3-O-(3-hydroxytetradecanoyl)-D-glucosamine\n",
      "glu gggagicolipa_c glucosyl-glucosyl-galactosyl-glucosyl-inner core oligosaccharide lipid A\n",
      "vio mDB_pdvnate_c Protodeoxyviolaceinate\n",
      "vio mDB_pdvnate_c Protodeoxyviolaceinate\n",
      "vio mDB_pvnate_c Protoviolaceinate\n",
      "vio mDB_pvnate_c Protoviolaceinate\n",
      "vio mDB_dvnate_c Deoxyviolaceinate\n",
      "vio mDB_dvnate_c Deoxyviolaceinate\n",
      "vio mDB_dvio_c Deoxyviolacein\n",
      "vio mDB_dvio_c Deoxyviolacein\n",
      "vio mDB_prodvio_c Prodeoxyviolacein\n",
      "vio mDB_prodvio_c Prodeoxyviolacein\n",
      "vio mDB_dvio_e Deoxyviolacein\n",
      "vio mDB_dvio_e Deoxyviolacein\n",
      "vio mDB_prodvio_e Prodeoxyviolacein\n",
      "vio mDB_prodvio_e Prodeoxyviolacein\n",
      "glu gthox_c Oxidized glutathione\n",
      "ser ps160_c Phosphatidylserine (dihexadecanoyl, n-C16:0)\n",
      "ser ps181_c Phosphatidylserine (dioctadec-11-enoyl, n-C18:1)\n",
      "ser ps140_c phosphatidylserine ditetradecanoyl\n",
      "ser ps120_c Phosphatidylserine (didodecanoyl, n-C12:0)\n",
      "ser ps161_c Phosphatidylserine (dihexadec-9-enoyl, n-C16:1)\n",
      "ser ps141_c phosphatidylserine ditetradec-7-enoyl\n",
      "glu akg_e 2-Oxoglutarate\n"
     ]
    }
   ],
   "source": [
    "for met in met_model.keys():\n",
    "    for miss in mismatch_metabolites:\n",
    "        query = miss.split(\"_\")[0]\n",
    "        if query in met_model[met]:\n",
    "            print(query, met, met_model[met])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3dd33a4-a720-4ca7-94c4-609b486038a8",
   "metadata": {},
   "source": [
    "Try to explore which one matches, sometimes need manual curation, and came up with this [table](../data/metabolite_map.csv). Hint: the amino acid starts with uppercase. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8ad51cb3-f443-490e-82a3-a92e29128a4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6a631c7b-a799-48ca-89b1-37a830cc0502",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>map_name</th>\n",
       "      <th>model_id</th>\n",
       "      <th>model_name</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>map_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2i3ip_c</th>\n",
       "      <td>2i3ip[c]</td>\n",
       "      <td>mDB_2i3ip_c</td>\n",
       "      <td>2 - imino - 3- (indol-3-yl)propanoate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34hpp_c</th>\n",
       "      <td>34hpp[c]</td>\n",
       "      <td>2h34hppr_c</td>\n",
       "      <td>p-hydroxyphenylpyruvate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dvio_c</th>\n",
       "      <td>dvio[c]</td>\n",
       "      <td>mDB_dvio_c</td>\n",
       "      <td>Deoxyviolacein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dvio_e</th>\n",
       "      <td>dvio[e]</td>\n",
       "      <td>mDB_dvio_e</td>\n",
       "      <td>Deoxyviolacein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dvnate_c</th>\n",
       "      <td>dvnate[c]</td>\n",
       "      <td>mDB_dvnate_c</td>\n",
       "      <td>Deoxyviolaceinate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gln_DASH_L_c</th>\n",
       "      <td>L-Glutamine</td>\n",
       "      <td>gln__L_c</td>\n",
       "      <td>L-Glutamine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>glu_DASH_L_c</th>\n",
       "      <td>L-Glutamate</td>\n",
       "      <td>glu__L_c</td>\n",
       "      <td>L-Glutamate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pdvnate_c</th>\n",
       "      <td>pdvnate[c]</td>\n",
       "      <td>mDB_pdvnate_c</td>\n",
       "      <td>Protodeoxyviolaceinate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>phe_DASH_L_c</th>\n",
       "      <td>phe-L[c]</td>\n",
       "      <td>phe__L_c</td>\n",
       "      <td>L-Phenylalanine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>phe_DASH_L_e</th>\n",
       "      <td>phe-L[e]</td>\n",
       "      <td>phe__L_e</td>\n",
       "      <td>L-Phenylalanine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>provio_c</th>\n",
       "      <td>provio[c]</td>\n",
       "      <td>mDB_prodvio_c</td>\n",
       "      <td>Prodeoxyviolacein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>provio_e</th>\n",
       "      <td>provio[e]</td>\n",
       "      <td>mDB_prodvio_e</td>\n",
       "      <td>Prodeoxyviolacein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pvnate_c</th>\n",
       "      <td>pvnate[c]</td>\n",
       "      <td>mDB_pvnate_c</td>\n",
       "      <td>Protoviolaceinate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ser_DASH_L_c</th>\n",
       "      <td>ser-L[c]</td>\n",
       "      <td>ser__L_c</td>\n",
       "      <td>L-Serine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trp_DASH_L_c</th>\n",
       "      <td>trp-L[c]</td>\n",
       "      <td>trp__L_c</td>\n",
       "      <td>L-Tryptophan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trp_DASH_L_e</th>\n",
       "      <td>trp-L[e]</td>\n",
       "      <td>trp__L_e</td>\n",
       "      <td>L-Tryptophan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tyr_DASH_L_c</th>\n",
       "      <td>tyr-L[c]</td>\n",
       "      <td>tyr__L_c</td>\n",
       "      <td>L-Tyrosine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tyr_DASH_L_e</th>\n",
       "      <td>tyr-L[e]</td>\n",
       "      <td>tyr__L_e</td>\n",
       "      <td>L-Tyrosine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vio_c</th>\n",
       "      <td>vio[c]</td>\n",
       "      <td>mDB_vio_c</td>\n",
       "      <td>Violacein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vio_e</th>\n",
       "      <td>vio[e]</td>\n",
       "      <td>mDB_vio_e</td>\n",
       "      <td>Violacein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vnate_c</th>\n",
       "      <td>vnate[c]</td>\n",
       "      <td>mDB_vnate_c</td>\n",
       "      <td>Violaceinate</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 map_name       model_id  \\\n",
       "map_id                                     \n",
       "2i3ip_c          2i3ip[c]    mDB_2i3ip_c   \n",
       "34hpp_c          34hpp[c]     2h34hppr_c   \n",
       "dvio_c            dvio[c]     mDB_dvio_c   \n",
       "dvio_e            dvio[e]     mDB_dvio_e   \n",
       "dvnate_c        dvnate[c]   mDB_dvnate_c   \n",
       "gln_DASH_L_c  L-Glutamine       gln__L_c   \n",
       "glu_DASH_L_c  L-Glutamate       glu__L_c   \n",
       "pdvnate_c      pdvnate[c]  mDB_pdvnate_c   \n",
       "phe_DASH_L_c     phe-L[c]       phe__L_c   \n",
       "phe_DASH_L_e     phe-L[e]       phe__L_e   \n",
       "provio_c        provio[c]  mDB_prodvio_c   \n",
       "provio_e        provio[e]  mDB_prodvio_e   \n",
       "pvnate_c        pvnate[c]   mDB_pvnate_c   \n",
       "ser_DASH_L_c     ser-L[c]       ser__L_c   \n",
       "trp_DASH_L_c     trp-L[c]       trp__L_c   \n",
       "trp_DASH_L_e     trp-L[e]       trp__L_e   \n",
       "tyr_DASH_L_c     tyr-L[c]       tyr__L_c   \n",
       "tyr_DASH_L_e     tyr-L[e]       tyr__L_e   \n",
       "vio_c              vio[c]      mDB_vio_c   \n",
       "vio_e              vio[e]      mDB_vio_e   \n",
       "vnate_c          vnate[c]    mDB_vnate_c   \n",
       "\n",
       "                                         model_name  \n",
       "map_id                                               \n",
       "2i3ip_c       2 - imino - 3- (indol-3-yl)propanoate  \n",
       "34hpp_c                     p-hydroxyphenylpyruvate  \n",
       "dvio_c                               Deoxyviolacein  \n",
       "dvio_e                               Deoxyviolacein  \n",
       "dvnate_c                          Deoxyviolaceinate  \n",
       "gln_DASH_L_c                            L-Glutamine  \n",
       "glu_DASH_L_c                            L-Glutamate  \n",
       "pdvnate_c                    Protodeoxyviolaceinate  \n",
       "phe_DASH_L_c                        L-Phenylalanine  \n",
       "phe_DASH_L_e                        L-Phenylalanine  \n",
       "provio_c                          Prodeoxyviolacein  \n",
       "provio_e                          Prodeoxyviolacein  \n",
       "pvnate_c                          Protoviolaceinate  \n",
       "ser_DASH_L_c                               L-Serine  \n",
       "trp_DASH_L_c                           L-Tryptophan  \n",
       "trp_DASH_L_e                           L-Tryptophan  \n",
       "tyr_DASH_L_c                             L-Tyrosine  \n",
       "tyr_DASH_L_e                             L-Tyrosine  \n",
       "vio_c                                     Violacein  \n",
       "vio_e                                     Violacein  \n",
       "vnate_c                                Violaceinate  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metabolite_map = pd.read_csv(\"../data/metabolite_map.csv\").dropna()\n",
    "metabolite_map = metabolite_map.set_index(\"map_id\")\n",
    "metabolite_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "35ab70dd-1603-4a97-ac1a-5a6e3683b6e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "replacing: 2i3ip_c --> mDB_2i3ip_c\n",
      "1577625 0 result: mDB_2i3ip_c\n",
      "------------------\n",
      "replacing: 2i3ip_c --> mDB_2i3ip_c\n",
      "1577626 0 result: mDB_2i3ip_c\n",
      "------------------\n",
      "replacing: 2i3ip_c --> mDB_2i3ip_c\n",
      "1577627 0 result: mDB_2i3ip_c\n",
      "------------------\n",
      "1577557 mDB_2i3ip_c mDB_2i3ip_c\n",
      "replacing: 34hpp_c --> 2h34hppr_c\n",
      "1577570 1 result: 2h34hppr_c\n",
      "------------------\n",
      "replacing: 34hpp_c --> 2h34hppr_c\n",
      "1577575 1 result: 2h34hppr_c\n",
      "------------------\n",
      "1577233 2h34hppr_c 2h34hppr_c\n",
      "replacing: dvio_c --> mDB_dvio_c\n",
      "1577640 2 result: mDB_dvio_c\n",
      "------------------\n",
      "replacing: dvio_c --> mDB_dvio_c\n",
      "1577641 1 result: mDB_dvio_c\n",
      "------------------\n",
      "1577660 mDB_dvio_c mDB_dvio_c\n",
      "replacing: dvio_e --> mDB_dvio_e\n",
      "1577641 0 result: mDB_dvio_e\n",
      "------------------\n",
      "replacing: dvio_e --> mDB_dvio_e\n",
      "1577642 0 result: mDB_dvio_e\n",
      "------------------\n",
      "1577666 mDB_dvio_e mDB_dvio_e\n",
      "replacing: dvnate_c --> mDB_dvnate_c\n",
      "1577638 6 result: mDB_dvnate_c\n",
      "------------------\n",
      "replacing: dvnate_c --> mDB_dvnate_c\n",
      "1577640 4 result: mDB_dvnate_c\n",
      "------------------\n",
      "1577646 mDB_dvnate_c mDB_dvnate_c\n",
      "replacing: gln_DASH_L_c --> gln__L_c\n",
      "1577573 2 result: gln__L_c\n",
      "------------------\n",
      "1577257 gln__L_c gln__L_c\n",
      "replacing: glu_DASH_L_c --> glu__L_c\n",
      "1577573 5 result: glu__L_c\n",
      "------------------\n",
      "replacing: glu_DASH_L_c --> glu__L_c\n",
      "1577574 2 result: glu__L_c\n",
      "------------------\n",
      "replacing: glu_DASH_L_c --> glu__L_c\n",
      "1577575 2 result: glu__L_c\n",
      "------------------\n",
      "1577259 glu__L_c glu__L_c\n",
      "1577264 glu__L_c glu__L_c\n",
      "1577270 glu__L_c glu__L_c\n",
      "replacing: pdvnate_c --> mDB_pdvnate_c\n",
      "1577626 3 result: mDB_pdvnate_c\n",
      "------------------\n",
      "replacing: pdvnate_c --> mDB_pdvnate_c\n",
      "1577630 4 result: mDB_pdvnate_c\n",
      "------------------\n",
      "replacing: pdvnate_c --> mDB_pdvnate_c\n",
      "1577638 4 result: mDB_pdvnate_c\n",
      "------------------\n",
      "1577566 mDB_pdvnate_c mDB_pdvnate_c\n",
      "replacing: phe_DASH_L_c --> phe__L_c\n",
      "1577574 3 result: phe__L_c\n",
      "------------------\n",
      "replacing: phe_DASH_L_c --> phe__L_c\n",
      "1577599 3 result: phe__L_c\n",
      "------------------\n",
      "1577265 phe__L_c phe__L_c\n",
      "replacing: phe_DASH_L_e --> phe__L_e\n",
      "1577599 0 result: phe__L_e\n",
      "------------------\n",
      "replacing: phe_DASH_L_e --> phe__L_e\n",
      "1577600 0 result: phe__L_e\n",
      "------------------\n",
      "1577414 phe__L_e phe__L_e\n",
      "replacing: provio_c --> mDB_prodvio_c\n",
      "1577643 2 result: mDB_prodvio_c\n",
      "------------------\n",
      "replacing: provio_c --> mDB_prodvio_c\n",
      "1577644 0 result: mDB_prodvio_c\n",
      "------------------\n",
      "1577675 mDB_prodvio_c mDB_prodvio_c\n",
      "replacing: provio_e --> mDB_prodvio_e\n",
      "1577644 1 result: mDB_prodvio_e\n",
      "------------------\n",
      "replacing: provio_e --> mDB_prodvio_e\n",
      "1577645 0 result: mDB_prodvio_e\n",
      "------------------\n",
      "1577681 mDB_prodvio_e mDB_prodvio_e\n",
      "replacing: pvnate_c --> mDB_pvnate_c\n",
      "1577630 5 result: mDB_pvnate_c\n",
      "------------------\n",
      "replacing: pvnate_c --> mDB_pvnate_c\n",
      "1577632 5 result: mDB_pvnate_c\n",
      "------------------\n",
      "replacing: pvnate_c --> mDB_pvnate_c\n",
      "1577643 3 result: mDB_pvnate_c\n",
      "------------------\n",
      "1577596 mDB_pvnate_c mDB_pvnate_c\n",
      "replacing: ser_DASH_L_c --> ser__L_c\n",
      "1577609 1 result: ser__L_c\n",
      "------------------\n",
      "replacing: ser_DASH_L_c --> ser__L_c\n",
      "1577611 1 result: ser__L_c\n",
      "------------------\n",
      "1577481 ser__L_c ser__L_c\n",
      "replacing: trp_DASH_L_c --> trp__L_c\n",
      "1577609 3 result: trp__L_c\n",
      "------------------\n",
      "replacing: trp_DASH_L_c --> trp__L_c\n",
      "1577611 3 result: trp__L_c\n",
      "------------------\n",
      "replacing: trp_DASH_L_c --> trp__L_c\n",
      "1577614 3 result: trp__L_c\n",
      "------------------\n",
      "replacing: trp_DASH_L_c --> trp__L_c\n",
      "1577619 3 result: trp__L_c\n",
      "------------------\n",
      "replacing: trp_DASH_L_c --> trp__L_c\n",
      "1577625 3 result: trp__L_c\n",
      "------------------\n",
      "1577482 trp__L_c trp__L_c\n",
      "replacing: trp_DASH_L_e --> trp__L_e\n",
      "1577619 0 result: trp__L_e\n",
      "------------------\n",
      "replacing: trp_DASH_L_e --> trp__L_e\n",
      "1577620 0 result: trp__L_e\n",
      "------------------\n",
      "1577529 trp__L_e trp__L_e\n",
      "replacing: tyr_DASH_L_c --> tyr__L_c\n",
      "1577575 3 result: tyr__L_c\n",
      "------------------\n",
      "replacing: tyr_DASH_L_c --> tyr__L_c\n",
      "1577601 3 result: tyr__L_c\n",
      "------------------\n",
      "1577271 tyr__L_c tyr__L_c\n",
      "replacing: tyr_DASH_L_e --> tyr__L_e\n",
      "1577601 0 result: tyr__L_e\n",
      "------------------\n",
      "replacing: tyr_DASH_L_e --> tyr__L_e\n",
      "1577602 0 result: tyr__L_e\n",
      "------------------\n",
      "1577423 tyr__L_e tyr__L_e\n",
      "replacing: vio_c --> mDB_vio_c\n",
      "1577633 4 result: mDB_vio_c\n",
      "------------------\n",
      "replacing: vio_c --> mDB_vio_c\n",
      "1577646 0 result: mDB_vio_c\n",
      "------------------\n",
      "1577622 mDB_vio_c mDB_vio_c\n",
      "replacing: vio_e --> mDB_vio_e\n",
      "1577646 1 result: mDB_vio_e\n",
      "------------------\n",
      "replacing: vio_e --> mDB_vio_e\n",
      "1577647 0 result: mDB_vio_e\n",
      "------------------\n",
      "1577688 mDB_vio_e mDB_vio_e\n",
      "replacing: vnate_c --> mDB_vnate_c\n",
      "1577632 4 result: mDB_vnate_c\n",
      "------------------\n",
      "replacing: vnate_c --> mDB_vnate_c\n",
      "1577633 2 result: mDB_vnate_c\n",
      "------------------\n",
      "1577614 mDB_vnate_c mDB_vnate_c\n"
     ]
    }
   ],
   "source": [
    "# replace metabolite value with model\n",
    "for query in metabolite_map.index:\n",
    "    for r in data[1][\"reactions\"]:\n",
    "        for num, m in enumerate(data[1][\"reactions\"][r][\"metabolites\"]):\n",
    "            if data[1][\"reactions\"][r][\"metabolites\"][num][\"bigg_id\"] == query:\n",
    "                print(\"replacing:\", query, \"-->\", metabolite_map.loc[query, \"model_id\"])\n",
    "                #print(r, num, data[1][\"reactions\"][r][\"metabolites\"][num][\"bigg_id\"])\n",
    "                data[1][\"reactions\"][r][\"metabolites\"][num][\"bigg_id\"] = metabolite_map.loc[query, \"model_id\"]\n",
    "                print(r, num, \"result:\", data[1][\"reactions\"][r][\"metabolites\"][num][\"bigg_id\"])\n",
    "                print(\"------------------\")\n",
    "    for n in data[1][\"nodes\"]:\n",
    "        if data[1][\"nodes\"][n][\"node_type\"] == \"metabolite\":\n",
    "            if data[1][\"nodes\"][n][\"bigg_id\"] == query:\n",
    "                data[1][\"nodes\"][n][\"bigg_id\"] = metabolite_map.loc[query, \"model_id\"]\n",
    "                data[1][\"nodes\"][n][\"name\"] = metabolite_map.loc[query, \"model_name\"]    \n",
    "                print(n, data[1][\"nodes\"][n][\"bigg_id\"], metabolite_map.loc[query, \"model_id\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ea79f3db-db0e-4624-888e-12909cd860af",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('../results/edited_map.json', 'w', encoding='utf-8') as f:\n",
    "    json.dump(data, f, ensure_ascii=False, indent=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2a0a8617-9c67-4fc7-9171-de234847d0e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "93c2639216d94e3baff217ee7270398b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Builder(reaction_data={'rxn12008_c': 0.00233685938934557, 'rxn00541_c': 0.0, 'rxn00225_c': 0.0, 'rxn01674_c': …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# map from author\n",
    "builder_scratch = Builder(\n",
    "    map_json = '../results/edited_map.json',\n",
    "    model = model,\n",
    "    reaction_data = s.fluxes\n",
    ")\n",
    "builder_scratch"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3623ce8a-b84c-46c8-af5c-81c71f721aeb",
   "metadata": {},
   "source": [
    "## Mapping Reactions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2b1d2f36-28e3-4fb6-92a5-1f06b5b65ece",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['name', 'bigg_id', 'reversibility', 'label_x', 'label_y', 'gene_reaction_rule', 'genes', 'metabolites', 'segments'])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What keys are available for each reactions?\n",
    "data[1][\"reactions\"][\"1576693\"].keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ae9f9c0f-b258-4696-9d16-138022407fa2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'name': 'Phosphoglycerate kinase',\n",
       " 'bigg_id': 'PGK',\n",
       " 'reversibility': True,\n",
       " 'label_x': 1065,\n",
       " 'label_y': 2715,\n",
       " 'gene_reaction_rule': 'b2926',\n",
       " 'genes': [{'bigg_id': 'b2926', 'name': 'pgk'}],\n",
       " 'metabolites': [{'coefficient': -1, 'bigg_id': '3pg_c'},\n",
       "  {'coefficient': 1, 'bigg_id': '13dpg_c'},\n",
       "  {'coefficient': -1, 'bigg_id': 'atp_c'},\n",
       "  {'coefficient': 1, 'bigg_id': 'adp_c'}],\n",
       " 'segments': {'291': {'from_node_id': '1576835',\n",
       "   'to_node_id': '1576836',\n",
       "   'b1': None,\n",
       "   'b2': None},\n",
       "  '292': {'from_node_id': '1576836',\n",
       "   'to_node_id': '1576834',\n",
       "   'b1': None,\n",
       "   'b2': None},\n",
       "  '293': {'from_node_id': '1576485',\n",
       "   'to_node_id': '1576835',\n",
       "   'b1': {'y': 2822.4341649025255, 'x': 1055},\n",
       "   'b2': {'y': 2789.230249470758, 'x': 1055}},\n",
       "  '294': {'from_node_id': '1576486',\n",
       "   'to_node_id': '1576835',\n",
       "   'b1': {'y': 2825, 'x': 1055},\n",
       "   'b2': {'y': 2790, 'x': 1055}},\n",
       "  '295': {'from_node_id': '1576834',\n",
       "   'to_node_id': '1576487',\n",
       "   'b1': {'y': 2650, 'x': 1055},\n",
       "   'b2': {'y': 2615, 'x': 1055}},\n",
       "  '296': {'from_node_id': '1576834',\n",
       "   'to_node_id': '1576488',\n",
       "   'b1': {'y': 2650.769750529242, 'x': 1055},\n",
       "   'b2': {'y': 2617.5658350974745, 'x': 1055}}}}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[1][\"reactions\"][\"1576693\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "0b01514d-5f87-4efb-a265-c357ffa04f1a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <table>\n",
       "            <tr>\n",
       "                <td><strong>Reaction identifier</strong></td><td>rxn12008_c</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Name</strong></td><td>rxn12008</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Memory address</strong></td>\n",
       "                <td>0x07f981e8450a0</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Stoichiometry</strong></td>\n",
       "                <td>\n",
       "                    <p style='text-align:right'>hepdp_c + ipdp_c --> octdp_c + ppi_c</p>\n",
       "                    <p style='text-align:right'>All-trans-Heptaprenyl diphosphate + Isopentenyl diphosphate --> All-trans-Octaprenyl diphosphate + Diphosphate</p>\n",
       "                </td>\n",
       "            </tr><tr>\n",
       "                <td><strong>GPR</strong></td><td>CV_0847 or CV_2691 or CV_3954</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Lower bound</strong></td><td>0.0</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Upper bound</strong></td><td>1000.0</td>\n",
       "            </tr>\n",
       "        </table>\n",
       "        "
      ],
      "text/plain": [
       "<Reaction rxn12008_c at 0x7f981e8450a0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.reactions.rxn12008_c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6a53ff53-01ba-4534-b867-13cdeb2daa8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "reaction_model = {}\n",
    "for r in model.reactions:\n",
    "    reaction_model[r.id] = {\"name\":r.name, \"metabolites\":[m.id for m in r.metabolites]}\n",
    "#reaction_model\n",
    "\n",
    "reaction_map = {}\n",
    "for r in data[1][\"reactions\"]:\n",
    "    reaction_map[data[1][\"reactions\"][r][\"bigg_id\"]] = {\n",
    "        \"name\" : data[1][\"reactions\"][r][\"name\"],\n",
    "        \"metabolites\": [i[\"bigg_id\"] for i in data[1][\"reactions\"][r][\"metabolites\"]],\n",
    "        \"node\": r}\n",
    "#reaction_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "46c9d081-6cb0-4f6f-8bf0-12070a78c38b",
   "metadata": {},
   "outputs": [],
   "source": [
    "mismatch_reactions = []\n",
    "for k in reaction_map.keys():\n",
    "    if not k in reaction_model.keys():\n",
    "        mismatch_reactions.append(k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b14bc339-842f-42da-8638-56e6b403af08",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "searching for PGK ...\n",
      "----------\n",
      "searching for GND ...\n",
      "----------\n",
      "searching for O2t ...\n",
      "O2t rxn05468_c\n",
      "----------\n",
      "searching for THD2 ...\n",
      "THD2 rxn10125_c\n",
      "----------\n",
      "searching for FUM ...\n",
      "FUM rxn00799_c\n",
      "----------\n",
      "searching for ICDHyr ...\n",
      "----------\n",
      "searching for PDH ...\n",
      "PDH rDB00149_c\n",
      "----------\n",
      "searching for PPC ...\n",
      "PPC rxn00251_c\n",
      "----------\n",
      "searching for ENO ...\n",
      "ENO rxn00459_c\n",
      "----------\n",
      "searching for PGI ...\n",
      "PGI rxn00558_c\n",
      "----------\n",
      "searching for NH4t ...\n",
      "NH4t rxn05466_c\n",
      "----------\n",
      "searching for FBP ...\n",
      "----------\n",
      "searching for ICL ...\n",
      "ICL rxn00336_c\n",
      "----------\n",
      "searching for ADK1 ...\n",
      "ADK1 rxn00097_c\n",
      "----------\n",
      "searching for EX_gln__L_e ...\n",
      "EX_gln__L_e EX_gln_L_e\n",
      "----------\n",
      "searching for TALA ...\n",
      "TALA rxn01333_c\n",
      "----------\n",
      "searching for PYK ...\n",
      "----------\n",
      "searching for GLUt2r ...\n",
      "GLUt2r rxn05297_c\n",
      "----------\n",
      "searching for EX_lac__D_e ...\n",
      "EX_lac__D_e EX_lac_D_e\n",
      "----------\n",
      "searching for RPE ...\n",
      "RPE rxn01116_c\n",
      "----------\n",
      "searching for SUCOAS ...\n",
      "SUCOAS rxn00285_c\n",
      "----------\n",
      "searching for PFK ...\n",
      "----------\n",
      "searching for EX_glu__L_e ...\n",
      "EX_glu__L_e EX_glu_L_e\n",
      "----------\n",
      "searching for TKT2 ...\n",
      "TKT2 rxn00785_c\n",
      "----------\n",
      "searching for GLNS ...\n",
      "GLNS rxn00187_c\n",
      "----------\n",
      "searching for NADTRHD ...\n",
      "NADTRHD rxn00083_c\n",
      "----------\n",
      "searching for AKGDH ...\n",
      "AKGDH rDB00036_c\n",
      "----------\n",
      "searching for PFL ...\n",
      "PFL rxn00157_c\n",
      "----------\n",
      "searching for PPCK ...\n",
      "----------\n",
      "searching for PIt2r ...\n",
      "PIt2r rxn05312_c\n",
      "----------\n",
      "searching for AKGt2r ...\n",
      "AKGt2r rDB00145_c\n",
      "----------\n",
      "searching for FBA ...\n",
      "FBA rxn00786_c\n",
      "----------\n",
      "searching for TPI ...\n",
      "TPI rxn00747_c\n",
      "----------\n",
      "searching for CYTBD ...\n",
      "CYTBD rxn10113_c\n",
      "----------\n",
      "searching for RPI ...\n",
      "RPI rxn00777_c\n",
      "----------\n",
      "searching for MALS ...\n",
      "MALS rxn00330_c\n",
      "----------\n",
      "searching for PTAr ...\n",
      "----------\n",
      "searching for GLNabc ...\n",
      "GLNabc rDB00147_c\n",
      "----------\n",
      "searching for ME1 ...\n",
      "----------\n",
      "searching for G6PDH2r ...\n",
      "G6PDH2r rxn00604_c\n",
      "----------\n",
      "searching for GLUN ...\n",
      "GLUN rxn00189_c\n",
      "----------\n",
      "searching for ATPM ...\n",
      "ATPM rxn00062_c\n",
      "----------\n",
      "searching for LDH_D ...\n",
      "LDH_D rDB00071_c\n",
      "----------\n",
      "searching for MDH ...\n",
      "MDH rxn00248_c\n",
      "----------\n",
      "searching for H2Ot ...\n",
      "H2Ot rxn05319_c\n",
      "----------\n",
      "searching for TKT1 ...\n",
      "TKT1 rxn01200_c\n",
      "----------\n",
      "searching for CO2t ...\n",
      "CO2t rxn05467_c\n",
      "----------\n",
      "searching for PPS ...\n",
      "PPS rxn00147_c\n",
      "----------\n",
      "searching for EX_glc__D_e ...\n",
      "EX_glc__D_e EX_glc_D_e\n",
      "----------\n",
      "searching for ETOHt2r ...\n",
      "ETOHt2r rDB00146_c\n",
      "----------\n",
      "searching for PGM ...\n",
      "PGM rxn01106_c\n",
      "----------\n",
      "searching for ACKr ...\n",
      "----------\n",
      "searching for GLUSy ...\n",
      "GLUSy rxn00085_c\n",
      "----------\n",
      "searching for FUMt2_2 ...\n",
      "FUMt2_2 rxn05561_c\n",
      "FUMt2_2 rxn10152_c\n",
      "----------\n",
      "searching for ACt2r ...\n",
      "ACt2r rDB00144_c\n",
      "----------\n",
      "searching for GLCpts ...\n",
      "GLCpts rxn05226_c\n",
      "----------\n",
      "searching for SUCCt3 ...\n",
      "SUCCt3 rxn10154_c\n",
      "SUCCt3 rxn05654_c\n",
      "----------\n",
      "searching for PGL ...\n",
      "PGL rxn01476_c\n",
      "----------\n",
      "searching for GAPD ...\n",
      "----------\n",
      "searching for SUCCt2_2 ...\n",
      "SUCCt2_2 rxn10154_c\n",
      "SUCCt2_2 rxn05654_c\n",
      "----------\n",
      "searching for GLUDy ...\n",
      "----------\n",
      "searching for ATPS4r ...\n",
      "ATPS4r rxn10042_c\n",
      "----------\n",
      "searching for CS ...\n",
      "CS rxn00256_c\n",
      "----------\n",
      "searching for PYRt2 ...\n",
      "PYRt2 rDB00150_c\n",
      "----------\n",
      "searching for ME2 ...\n",
      "ME2 rxn00161_c\n",
      "----------\n",
      "searching for ACALD ...\n",
      "ACALD rxn00171_c\n",
      "----------\n",
      "searching for ACALDt ...\n",
      "ACALDt rDB00143_c\n",
      "----------\n",
      "searching for ALCD2x ...\n",
      "ALCD2x rxn00543_c\n",
      "----------\n",
      "searching for FORt2 ...\n",
      "FORt2 rxn05559_c\n",
      "----------\n",
      "searching for FORti ...\n",
      "----------\n",
      "searching for FRD7 ...\n",
      "FRD7 rxn09272_c\n",
      "----------\n",
      "searching for FRUpts2 ...\n",
      "----------\n",
      "searching for MALt2_2 ...\n",
      "MALt2_2 rxn10153_c\n",
      "----------\n",
      "searching for EX_mal__L_e ...\n",
      "EX_mal__L_e EX_mal_L_e\n",
      "----------\n",
      "searching for NADH16 ...\n",
      "NADH16 rxn10122_c\n",
      "----------\n",
      "searching for SUCDi ...\n",
      "SUCDi rxn09272_c\n",
      "----------\n",
      "searching for D_LACt2 ...\n",
      "----------\n",
      "searching for BIOMASS_Ecoli_core_w_GAM ...\n",
      "----------\n",
      "searching for ACONTa ...\n",
      "ACONTa rxn00974_c\n",
      "----------\n",
      "searching for ACONTb ...\n",
      "ACONTb rxn01388_c\n",
      "----------\n",
      "searching for DDPA ...\n",
      "----------\n",
      "searching for DHQS ...\n",
      "----------\n",
      "searching for DHQD ...\n",
      "DHQD rxn02213_c\n",
      "----------\n",
      "searching for SHK3Dr ...\n",
      "SHK3Dr rxn01740_c\n",
      "----------\n",
      "searching for SHKK ...\n",
      "----------\n",
      "searching for PSCVT ...\n",
      "----------\n",
      "searching for CHORS ...\n",
      "----------\n",
      "searching for CHORM ...\n",
      "CHORM rDB00002_c\n",
      "----------\n",
      "searching for PPND ...\n",
      "PPND rxn01268_c\n",
      "----------\n",
      "searching for PPNDH ...\n",
      "PPNDH rxn01000_c\n",
      "----------\n",
      "searching for ANS ...\n",
      "ANS rxn00727_c\n",
      "----------\n",
      "searching for PHETA1 ...\n",
      "PHETA1 rxn00493_c\n",
      "----------\n",
      "searching for TYRTA ...\n",
      "TYRTA rxn00527_c\n",
      "----------\n",
      "searching for ANPRT ...\n",
      "ANPRT rxn00791_c\n",
      "----------\n",
      "searching for PRAIi ...\n",
      "PRAIi rxn02508_c\n",
      "----------\n",
      "searching for IGPS ...\n",
      "IGPS rxn02507_c\n",
      "----------\n",
      "searching for PHEt2r ...\n",
      "----------\n",
      "searching for EX_phe ...\n",
      "EX_phe EX_phe_L_e\n",
      "----------\n",
      "searching for TYRt2r ...\n",
      "TYRt2r rDB00152_c\n",
      "----------\n",
      "searching for EX_tyr ...\n",
      "EX_tyr EX_tyr_L_e\n",
      "----------\n",
      "searching for TRPS1 ...\n",
      "TRPS1 rxn01964_c\n",
      "----------\n",
      "searching for TRPS3 ...\n",
      "TRPS3 rxn01682_c\n",
      "----------\n",
      "searching for TRPS2 ...\n",
      "TRPS2 rxn00474_c\n",
      "----------\n",
      "searching for TRPAS2 ...\n",
      "TRPAS2 rxn00473_c\n",
      "----------\n",
      "searching for TRPt2r ...\n",
      "TRPt2r rDB00151_c\n",
      "----------\n",
      "searching for EX_trp ...\n",
      "EX_trp EX_trp_L_e\n",
      "----------\n",
      "searching for rxnvio1 ...\n",
      "rxnvio1 rDB00091_c\n",
      "----------\n",
      "searching for rxnvio2 ...\n",
      "rxnvio2 rDB00092_c\n",
      "----------\n",
      "searching for rxnvio6 ...\n",
      "----------\n",
      "searching for rxnvio3 ...\n",
      "rxnvio3 rDB00093_c\n",
      "----------\n",
      "searching for rxnvio4 ...\n",
      "rxnvio4 rDB00094_c\n",
      "----------\n",
      "searching for rxnvio5 ...\n",
      "rxnvio5 rDB00095_c\n",
      "----------\n",
      "searching for DF_chpy ...\n",
      "----------\n",
      "searching for Ex_chpy_e ...\n",
      "----------\n",
      "searching for rxnvio7 ...\n",
      "rxnvio7 rDB00096_c\n",
      "----------\n",
      "searching for rxnvio8 ...\n",
      "rxnvio8 rDB00097_c\n",
      "----------\n",
      "searching for DF_dvio ...\n",
      "----------\n",
      "searching for Ex_dvio_e ...\n",
      "Ex_dvio_e EX_dvio_e\n",
      "----------\n",
      "searching for rxnvio9 ...\n",
      "----------\n",
      "searching for DF_provio ...\n",
      "DF_provio rDB00100_c\n",
      "----------\n",
      "searching for Ex_provio_e ...\n",
      "Ex_provio_e EX_prodvio_e\n",
      "----------\n",
      "searching for DF_vio ...\n",
      "----------\n",
      "searching for Ex_vio_e ...\n",
      "Ex_vio_e EX_vio_e\n",
      "----------\n"
     ]
    }
   ],
   "source": [
    "reaction_table = []\n",
    "not_found = {}\n",
    "for k in mismatch_reactions:\n",
    "    print(\"searching for\", k, \"...\")\n",
    "    query = set(reaction_map[k][\"metabolites\"])\n",
    "    for r in reaction_model:\n",
    "        target = set(reaction_model[r][\"metabolites\"])\n",
    "        if query == target:\n",
    "            print(k, r)\n",
    "            reaction_table.append({\"map_id\":k,\n",
    "                                   \"map_name\": reaction_map[k][\"name\"],\n",
    "                                   \"map_metabolites\": reaction_map[k][\"metabolites\"],\n",
    "                                   \"map_node\": reaction_map[k][\"node\"],\n",
    "                                   \"model_id\":r,\n",
    "                                   \"model_name\": reaction_model[r][\"name\"],\n",
    "                                   \"model_metabolites\": reaction_model[r][\"metabolites\"],\n",
    "                                   })\n",
    "        else:\n",
    "            not_found[k] = \"Not Found\"\n",
    "    print(\"----------\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "131f21dd-33c4-4874-997a-31ff2fadab73",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>map_id</th>\n",
       "      <th>map_name</th>\n",
       "      <th>map_metabolites</th>\n",
       "      <th>map_node</th>\n",
       "      <th>model_id</th>\n",
       "      <th>model_name</th>\n",
       "      <th>model_metabolites</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>O2t</td>\n",
       "      <td>O2 transport  diffusion</td>\n",
       "      <td>[o2_c, o2_e]</td>\n",
       "      <td>1576695</td>\n",
       "      <td>rxn05468_c</td>\n",
       "      <td>O2 transport via diffusion</td>\n",
       "      <td>[o2_e, o2_c]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>THD2</td>\n",
       "      <td>NAD P  transhydrogenase</td>\n",
       "      <td>[h_e, nadp_c, nadh_c, nadph_c, h_c, nad_c]</td>\n",
       "      <td>1576696</td>\n",
       "      <td>rxn10125_c</td>\n",
       "      <td>NADP transhydrogenase</td>\n",
       "      <td>[nadh_c, nadp_c, h_e, h_c, nad_c, nadph_c]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FUM</td>\n",
       "      <td>Fumarase</td>\n",
       "      <td>[fum_c, h2o_c, mal__L_c]</td>\n",
       "      <td>1576697</td>\n",
       "      <td>rxn00799_c</td>\n",
       "      <td>S-Malate hydro-lyase</td>\n",
       "      <td>[mal__L_c, fum_c, h2o_c]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>PDH</td>\n",
       "      <td>Pyruvate dehydrogenase</td>\n",
       "      <td>[nadh_c, coa_c, pyr_c, accoa_c, nad_c, co2_c]</td>\n",
       "      <td>1576699</td>\n",
       "      <td>rDB00149_c</td>\n",
       "      <td>pyruvate dehydrogenase</td>\n",
       "      <td>[coa_c, nad_c, pyr_c, co2_c, accoa_c, nadh_c]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>PPC</td>\n",
       "      <td>Phosphoenolpyruvate carboxylase</td>\n",
       "      <td>[h2o_c, oaa_c, h_c, pep_c, pi_c, co2_c]</td>\n",
       "      <td>1576700</td>\n",
       "      <td>rxn00251_c</td>\n",
       "      <td>Orthophosphate oxaloacetate carboxyl-lyase pho...</td>\n",
       "      <td>[co2_c, h2o_c, pep_c, h_c, pi_c, oaa_c]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>rxnvio8</td>\n",
       "      <td>rxnvio8</td>\n",
       "      <td>[o2_c, h2o_c, mDB_dvio_c, h_c, mDB_dvnate_c, c...</td>\n",
       "      <td>1577640</td>\n",
       "      <td>rDB00097_c</td>\n",
       "      <td>Deoxyviolacein spontaneous synthesis</td>\n",
       "      <td>[h_c, o2_c, mDB_dvnate_c, co2_c, h2o_c, mDB_dv...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>Ex_dvio_e</td>\n",
       "      <td>Ex_dvio[e]</td>\n",
       "      <td>[mDB_dvio_e]</td>\n",
       "      <td>1577642</td>\n",
       "      <td>EX_dvio_e</td>\n",
       "      <td>Deoxyviolacein Exchange</td>\n",
       "      <td>[mDB_dvio_e]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>DF_provio</td>\n",
       "      <td>DF_provio</td>\n",
       "      <td>[mDB_prodvio_c, mDB_prodvio_e]</td>\n",
       "      <td>1577644</td>\n",
       "      <td>rDB00100_c</td>\n",
       "      <td>Diffusion of prodeoxyviolacein</td>\n",
       "      <td>[mDB_prodvio_c, mDB_prodvio_e]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>Ex_provio_e</td>\n",
       "      <td>Ex_provio[e]</td>\n",
       "      <td>[mDB_prodvio_e]</td>\n",
       "      <td>1577645</td>\n",
       "      <td>EX_prodvio_e</td>\n",
       "      <td>Prodeoxyviolacein Exchange</td>\n",
       "      <td>[mDB_prodvio_e]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>Ex_vio_e</td>\n",
       "      <td>Ex_vio[e]</td>\n",
       "      <td>[mDB_vio_e]</td>\n",
       "      <td>1577647</td>\n",
       "      <td>EX_vio_e</td>\n",
       "      <td>Violacein Exchange</td>\n",
       "      <td>[mDB_vio_e]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>92 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         map_id                         map_name  \\\n",
       "0           O2t         O2 transport  diffusion    \n",
       "1          THD2          NAD P  transhydrogenase   \n",
       "2           FUM                         Fumarase   \n",
       "3           PDH           Pyruvate dehydrogenase   \n",
       "4           PPC  Phosphoenolpyruvate carboxylase   \n",
       "..          ...                              ...   \n",
       "93      rxnvio8                          rxnvio8   \n",
       "94    Ex_dvio_e                       Ex_dvio[e]   \n",
       "95    DF_provio                        DF_provio   \n",
       "96  Ex_provio_e                     Ex_provio[e]   \n",
       "97     Ex_vio_e                        Ex_vio[e]   \n",
       "\n",
       "                                      map_metabolites map_node      model_id  \\\n",
       "0                                        [o2_c, o2_e]  1576695    rxn05468_c   \n",
       "1          [h_e, nadp_c, nadh_c, nadph_c, h_c, nad_c]  1576696    rxn10125_c   \n",
       "2                            [fum_c, h2o_c, mal__L_c]  1576697    rxn00799_c   \n",
       "3       [nadh_c, coa_c, pyr_c, accoa_c, nad_c, co2_c]  1576699    rDB00149_c   \n",
       "4             [h2o_c, oaa_c, h_c, pep_c, pi_c, co2_c]  1576700    rxn00251_c   \n",
       "..                                                ...      ...           ...   \n",
       "93  [o2_c, h2o_c, mDB_dvio_c, h_c, mDB_dvnate_c, c...  1577640    rDB00097_c   \n",
       "94                                       [mDB_dvio_e]  1577642     EX_dvio_e   \n",
       "95                     [mDB_prodvio_c, mDB_prodvio_e]  1577644    rDB00100_c   \n",
       "96                                    [mDB_prodvio_e]  1577645  EX_prodvio_e   \n",
       "97                                        [mDB_vio_e]  1577647      EX_vio_e   \n",
       "\n",
       "                                           model_name  \\\n",
       "0                          O2 transport via diffusion   \n",
       "1                               NADP transhydrogenase   \n",
       "2                                S-Malate hydro-lyase   \n",
       "3                              pyruvate dehydrogenase   \n",
       "4   Orthophosphate oxaloacetate carboxyl-lyase pho...   \n",
       "..                                                ...   \n",
       "93               Deoxyviolacein spontaneous synthesis   \n",
       "94                            Deoxyviolacein Exchange   \n",
       "95                     Diffusion of prodeoxyviolacein   \n",
       "96                         Prodeoxyviolacein Exchange   \n",
       "97                                 Violacein Exchange   \n",
       "\n",
       "                                    model_metabolites  \n",
       "0                                        [o2_e, o2_c]  \n",
       "1          [nadh_c, nadp_c, h_e, h_c, nad_c, nadph_c]  \n",
       "2                            [mal__L_c, fum_c, h2o_c]  \n",
       "3       [coa_c, nad_c, pyr_c, co2_c, accoa_c, nadh_c]  \n",
       "4             [co2_c, h2o_c, pep_c, h_c, pi_c, oaa_c]  \n",
       "..                                                ...  \n",
       "93  [h_c, o2_c, mDB_dvnate_c, co2_c, h2o_c, mDB_dv...  \n",
       "94                                       [mDB_dvio_e]  \n",
       "95                     [mDB_prodvio_c, mDB_prodvio_e]  \n",
       "96                                    [mDB_prodvio_e]  \n",
       "97                                        [mDB_vio_e]  \n",
       "\n",
       "[92 rows x 7 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_matching_reactions = pd.DataFrame(reaction_table)\n",
    "# more than 1 match\n",
    "drop = df_matching_reactions.map_id.value_counts()[df_matching_reactions.map_id.value_counts() > 1]\n",
    "idx_filter = []\n",
    "for idx in df_matching_reactions.index:\n",
    "    if not df_matching_reactions.loc[idx, \"map_id\"] in drop:\n",
    "        idx_filter.append(idx)\n",
    "df_matching_reactions.loc[idx_filter, :]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "c2ebdb03-a4d9-47cb-9e34-930eeead8479",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rxn09272_c\n"
     ]
    }
   ],
   "source": [
    "#to do\n",
    "## replace model reaction id with map\n",
    "# load Chromobacterium model\n",
    "model = load_model('../data/iDB858_edited.xml')\n",
    "for idx in df_matching_reactions.loc[idx_filter, :].index:\n",
    "    target_model = df_matching_reactions.loc[idx, \"model_id\"]\n",
    "    try:\n",
    "        model.reactions.get_by_id(target_model).id = df_matching_reactions.loc[idx, \"map_id\"]\n",
    "    except KeyError:\n",
    "        print(target_model)   \n",
    "    data[1][\"reactions\"][df_matching_reactions.loc[idx, \"map_node\"]][\"name\"] = df_matching_reactions.loc[idx, \"model_name\"]\n",
    "\n",
    "with open('../results/edited_map_reaction_curated_phase1.json', 'w', encoding='utf-8') as f:\n",
    "    json.dump(data, f, ensure_ascii=False, indent=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "94402a2c-6ced-48b7-81ce-d81fb2f384c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2515998481207547"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# simulasi model\n",
    "s = fba(model)\n",
    "flux = s.fluxes.to_frame()\n",
    "s.objective_value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b7c0aa11-66e6-48a8-ba03-acb06ec94d90",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e4559c2a3c0744beaf4c86bf8df8f00f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Builder(reaction_data={'rxn12008_c': 0.00233685938934557, 'rxn00541_c': 0.0, 'rxn00225_c': 0.0, 'rxn01674_c': …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# map from author\n",
    "builder_scratch = Builder(\n",
    "    map_json = '../results/edited_map_reaction_curated_phase1.json',\n",
    "    model = model,\n",
    "    reaction_data = s.fluxes\n",
    ")\n",
    "builder_scratch"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e574f17-0d0b-4de8-89fb-aa6e3401e718",
   "metadata": {},
   "source": [
    "## Final Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "872e6a0b-0734-4e40-b277-a3d52f11c25c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SUCCt2_2    2\n",
       "SUCCt3      2\n",
       "FUMt2_2     2\n",
       "Name: map_id, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# double reaction with the same molecules, decide which one is which\n",
    "drop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "26d58508-2330-4718-acd8-316bc87d0802",
   "metadata": {},
   "outputs": [],
   "source": [
    "drop = df_matching_reactions.map_id.value_counts()[df_matching_reactions.map_id.value_counts() > 1]\n",
    "idx_filter = []\n",
    "for idx in df_matching_reactions.index:\n",
    "    if df_matching_reactions.loc[idx, \"map_id\"] in drop:\n",
    "        idx_filter.append(idx)\n",
    "df_matching_reactions.loc[idx_filter, :].to_csv(\"../tables/double_reactions.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7752312c-e318-4370-9385-afb513e5868d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['FUMt2_2', 'SUCCt3', 'SUCCt2_2'], dtype=object)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_matching_reactions.loc[idx_filter, :].map_id.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "8a8341c7-47c3-4ded-af2e-92da36eccb33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['rxn05561_c', 'rxn10152_c', 'rxn10154_c', 'rxn05654_c'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_matching_reactions.loc[idx_filter, :].model_id.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "273db9a0-7352-4994-83f0-6168631c50f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "32\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['PGK',\n",
       " 'GND',\n",
       " 'ICDHyr',\n",
       " 'FBP',\n",
       " 'PYK',\n",
       " 'PFK',\n",
       " 'PPCK',\n",
       " 'PTAr',\n",
       " 'ME1',\n",
       " 'ACKr',\n",
       " 'FUMt2_2',\n",
       " 'SUCCt3',\n",
       " 'GAPD',\n",
       " 'SUCCt2_2',\n",
       " 'GLUDy',\n",
       " 'FORti',\n",
       " 'FRUpts2',\n",
       " 'SUCDi',\n",
       " 'D_LACt2',\n",
       " 'BIOMASS_Ecoli_core_w_GAM',\n",
       " 'DDPA',\n",
       " 'DHQS',\n",
       " 'SHKK',\n",
       " 'PSCVT',\n",
       " 'CHORS',\n",
       " 'PHEt2r',\n",
       " 'rxnvio6',\n",
       " 'DF_chpy',\n",
       " 'Ex_chpy_e',\n",
       " 'DF_dvio',\n",
       " 'rxnvio9',\n",
       " 'DF_vio']"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reaction_model = {}\n",
    "for r in model.reactions:\n",
    "    reaction_model[r.id] = {\"name\":r.name, \"metabolites\":[m.id for m in r.metabolites]}\n",
    "#reaction_model\n",
    "\n",
    "reaction_map = {}\n",
    "for r in data[1][\"reactions\"]:\n",
    "    reaction_map[data[1][\"reactions\"][r][\"bigg_id\"]] = {\n",
    "        \"name\" : data[1][\"reactions\"][r][\"name\"],\n",
    "        \"metabolites\": [i[\"bigg_id\"] for i in data[1][\"reactions\"][r][\"metabolites\"]],\n",
    "        \"node\": r}\n",
    "#reaction_map\n",
    "\n",
    "mismatch_reactions = []\n",
    "for k in reaction_map.keys():\n",
    "    if not k in reaction_model.keys():\n",
    "        mismatch_reactions.append(k)\n",
    "print(len(mismatch_reactions))\n",
    "mismatch_reactions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "25cfbf96-7cac-42b5-804c-ad54028b1157",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_missing_reactions = []\n",
    "for i in data[1][\"reactions\"]:\n",
    "    if data[1][\"reactions\"][i][\"bigg_id\"] in mismatch_reactions:\n",
    "        df_missing_reactions.append(data[1][\"reactions\"][i])\n",
    "df_missing = pd.DataFrame(df_missing_reactions)\n",
    "df_missing = df_missing.loc[:, [\"name\", \"bigg_id\", \"gene_reaction_rule\", \"genes\", \"metabolites\"]]\n",
    "df_missing.to_csv(\"../tables/missing_on_map.csv\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "4629cc77-9360-41b1-b528-0256741157d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "model_reactions = []\n",
    "for i in model.reactions:\n",
    "    d = {\"name\":i.name, \n",
    "         \"bigg_id\":i.id,\n",
    "         \"metabolites\":[{\"coefficient\":i.get_coefficient(x), \"bigg_id\":x.id} for x in i.metabolites]}\n",
    "    model_reactions.append(d)\n",
    "df_model_reactions = pd.DataFrame(model_reactions)\n",
    "df_model_reactions.to_csv(\"../tables/all_reactions_in_model.csv\")"
   ]
  }
 ],
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