docs/notebooks/talk2knowledgegraphs/tutorial_biobridge_primekg_loader.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tutorial: BioBridge-PrimeKG Loader"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this tutorial, we will explain how to load BioBridge-PrimeKG dataset, which is a dataset for cross-modality prediction using PrimeKG as the knowledge graph. \n",
    "\n",
    "Prior information about the BioBridge-PrimeKG dataaset can be found in the following repositories:\n",
    "- https://github.com/RyanWangZf/BioBridge\n",
    "- https://arxiv.org/pdf/2310.03320"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We first need to import the necessary libraries as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\mulyadi\\Repo\\AIAgents4Pharma\\venv\\Lib\\site-packages\\pydantic\\_internal\\_fields.py:132: UserWarning: Field \"model_id\" in SysBioModel has conflict with protected namespace \"model_\".\n",
      "\n",
      "You may be able to resolve this warning by setting `model_config['protected_namespaces'] = ()`.\n",
      "  warnings.warn(\n",
      "c:\\Users\\mulyadi\\Repo\\AIAgents4Pharma\\venv\\Lib\\site-packages\\pydantic\\_internal\\_fields.py:132: UserWarning: Field \"model_id\" in BasicoModel has conflict with protected namespace \"model_\".\n",
      "\n",
      "You may be able to resolve this warning by setting `model_config['protected_namespaces'] = ()`.\n",
      "  warnings.warn(\n",
      "c:\\Users\\mulyadi\\Repo\\AIAgents4Pharma\\venv\\Lib\\site-packages\\pydantic\\_internal\\_fields.py:132: UserWarning: Field \"model_data\" in SimulateModelInput has conflict with protected namespace \"model_\".\n",
      "\n",
      "You may be able to resolve this warning by setting `model_config['protected_namespaces'] = ()`.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "# Import necessary libraries\n",
    "import sys\n",
    "sys.path.append('../../..')\n",
    "from aiagents4pharma.talk2knowledgegraphs.datasets.biobridge_primekg import BioBridgePrimeKG"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load BioBridge-PrimeKG"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `BioBridgePrimeKG` allows to load the data from related Github repository if the data is not available locally. \n",
    "\n",
    "Otherwise, the data is loaded from the local directory as defined in the `local_dir` and `primekg_dir`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define biobridge primekg data by providing a local directory where the data is stored\n",
    "biobridge_data = BioBridgePrimeKG(primekg_dir=\"../../../../data/primekg_test/\",\n",
    "                                  local_dir=\"../../../../data/biobridge_primekg_test/\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To load the dataframes of BioBridge and its split, we just need to call a method as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading PrimeKG dataset...\n",
      "Loading nodes of PrimeKG dataset ...\n",
      "Downloading node file from https://dataverse.harvard.edu/api/access/datafile/6180617\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 8.89M/8.89M [00:01<00:00, 6.39MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading edges of PrimeKG dataset ...\n",
      "Downloading edge file from https://dataverse.harvard.edu/api/access/datafile/6180616\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 387M/387M [12:53<00:00, 500kiB/s]  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading data config file of BioBridgePrimeKG...\n",
      "Downloading data_config.json from https://raw.githubusercontent.com/RyanWangZf/BioBridge/refs/heads/main/data/BindData/data_config.json to ../../../../data/biobridge_primekg_test/...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "1.03kiB [00:00, 344kiB/s]                 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Building node embeddings...\n",
      "Downloading protein.pkl from https://media.githubusercontent.com/media/RyanWangZf/BioBridge/refs/heads/main/data/embeddings/esm2b_unimo_pubmedbert/protein.pkl to ../../../../data/biobridge_primekg_test/embeddings...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 197M/197M [02:26<00:00, 1.34MiB/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading mf.pkl from https://media.githubusercontent.com/media/RyanWangZf/BioBridge/refs/heads/main/data/embeddings/esm2b_unimo_pubmedbert/mf.pkl to ../../../../data/biobridge_primekg_test/embeddings...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 34.3M/34.3M [00:12<00:00, 2.68MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading cc.pkl from https://media.githubusercontent.com/media/RyanWangZf/BioBridge/refs/heads/main/data/embeddings/esm2b_unimo_pubmedbert/cc.pkl to ../../../../data/biobridge_primekg_test/embeddings...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 12.5M/12.5M [00:01<00:00, 9.26MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading bp.pkl from https://media.githubusercontent.com/media/RyanWangZf/BioBridge/refs/heads/main/data/embeddings/esm2b_unimo_pubmedbert/bp.pkl to ../../../../data/biobridge_primekg_test/embeddings...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 85.9M/85.9M [01:11<00:00, 1.20MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading drug.pkl from https://media.githubusercontent.com/media/RyanWangZf/BioBridge/refs/heads/main/data/embeddings/esm2b_unimo_pubmedbert/drug.pkl to ../../../../data/biobridge_primekg_test/embeddings...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 28.7M/28.7M [00:02<00:00, 10.7MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading disease.pkl from https://media.githubusercontent.com/media/RyanWangZf/BioBridge/refs/heads/main/data/embeddings/esm2b_unimo_pubmedbert/disease.pkl to ../../../../data/biobridge_primekg_test/embeddings...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 53.1M/53.1M [00:39<00:00, 1.34MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Building full triplets...\n",
      "Downloading protein.csv from https://media.githubusercontent.com/media/RyanWangZf/BioBridge/refs/heads/main/data/Processed/protein.csv to ../../../../data/biobridge_primekg_test/processed...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 11.7M/11.7M [00:01<00:00, 9.19MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading mf.csv from https://media.githubusercontent.com/media/RyanWangZf/BioBridge/refs/heads/main/data/Processed/molecular.csv to ../../../../data/biobridge_primekg_test/processed...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 2.24M/2.24M [00:00<00:00, 2.81MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading cc.csv from https://media.githubusercontent.com/media/RyanWangZf/BioBridge/refs/heads/main/data/Processed/cellular.csv to ../../../../data/biobridge_primekg_test/processed...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1.05M/1.05M [00:00<00:00, 5.83MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading bp.csv from https://media.githubusercontent.com/media/RyanWangZf/BioBridge/refs/heads/main/data/Processed/biological.csv to ../../../../data/biobridge_primekg_test/processed...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 6.79M/6.79M [00:01<00:00, 5.03MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading drug.csv from https://media.githubusercontent.com/media/RyanWangZf/BioBridge/refs/heads/main/data/Processed/drug.csv to ../../../../data/biobridge_primekg_test/processed...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 9.47M/9.47M [00:01<00:00, 6.20MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading disease.csv from https://media.githubusercontent.com/media/RyanWangZf/BioBridge/refs/heads/main/data/Processed/disease.csv to ../../../../data/biobridge_primekg_test/processed...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 11.4M/11.4M [00:02<00:00, 5.38MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Building train-test split...\n",
      "Number of 1 nodes in train: 16918\n",
      "Number of 1 nodes in test: 1879\n",
      "Number of 6 nodes in train: 6084\n",
      "Number of 6 nodes in test: 675\n",
      "Number of 2 nodes in train: 15349\n",
      "Number of 2 nodes in test: 1705\n",
      "Number of 0 nodes in train: 24669\n",
      "Number of 0 nodes in test: 2740\n",
      "Number of 5 nodes in train: 9856\n",
      "Number of 5 nodes in test: 1095\n",
      "Number of 7 nodes in train: 3610\n",
      "Number of 7 nodes in test: 401\n"
     ]
    }
   ],
   "source": [
    "# Invoke a method to load the data\n",
    "biobridge_data.load_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a result, we obtained several processed files in the local directory as explained in the subsequent sections."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check initial PrimeKG Dataframes "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Firstly, we can get the initial PrimeKG data by invoking the method `get_primekg()` and further check the dataframes of nodes and edges."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the initial data of PrimeKG\n",
    "primekg_nodes = biobridge_data.get_primekg().get_nodes()\n",
    "primekg_edges = biobridge_data.get_primekg().get_edges()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "   node_index node_name node_source node_id     node_type\n",
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      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check PrimeKG nodes\n",
    "primekg_nodes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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     "data": {
      "text/plain": [
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     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the dimensions of the PrimeKG nodes\n",
    "primekg_nodes.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
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       "   head_index head_name head_source head_id     head_type  tail_index  \\\n",
       "0           0    PHYHIP        NCBI    9796  gene/protein        8889   \n",
       "1           1    GPANK1        NCBI    7918  gene/protein        2798   \n",
       "2           2     ZRSR2        NCBI    8233  gene/protein        5646   \n",
       "3           3      NRF1        NCBI    4899  gene/protein       11592   \n",
       "4           4     PI4KA        NCBI    5297  gene/protein        2122   \n",
       "\n",
       "  tail_name tail_source tail_id     tail_type display_relation  \\\n",
       "0     KIF15        NCBI   56992  gene/protein              ppi   \n",
       "1     PNMA1        NCBI    9240  gene/protein              ppi   \n",
       "2     TTC33        NCBI   23548  gene/protein              ppi   \n",
       "3    MAN1B1        NCBI   11253  gene/protein              ppi   \n",
       "4     RGS20        NCBI    8601  gene/protein              ppi   \n",
       "\n",
       "          relation  \n",
       "0  protein_protein  \n",
       "1  protein_protein  \n",
       "2  protein_protein  \n",
       "3  protein_protein  \n",
       "4  protein_protein  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check PrimeKG edges\n",
    "primekg_edges.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8100498, 12)"
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     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the dimensions of the PrimeKG edges\n",
    "primekg_edges.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check BioBridge-PrimeKG Data Config"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "BioBridgePrimeKG class provides a method to load the dataconfig file which contains the following information:\n",
    "- `node_type` : The node type mapping\n",
    "- `relation_type` : The relation type mapping\n",
    "- `emb_dim` : The embedding dimension (pre-loaded embeddings from the repository)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['node_type', 'relation_type', 'emb_dim'])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "biobridge_data.get_data_config().keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'biological_process': 0,\n",
       " 'gene/protein': 1,\n",
       " 'disease': 2,\n",
       " 'effect/phenotype': 3,\n",
       " 'anatomy': 4,\n",
       " 'molecular_function': 5,\n",
       " 'drug': 6,\n",
       " 'cellular_component': 7,\n",
       " 'pathway': 8,\n",
       " 'exposure': 9}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the node type within data config of the BioBridge PrimeKG\n",
    "biobridge_data.get_data_config()['node_type']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'expression present': 0,\n",
       " 'synergistic interaction': 1,\n",
       " 'interacts with': 2,\n",
       " 'ppi': 3,\n",
       " 'phenotype present': 4,\n",
       " 'parent-child': 5,\n",
       " 'associated with': 6,\n",
       " 'side effect': 7,\n",
       " 'contraindication': 8,\n",
       " 'expression absent': 9,\n",
       " 'target': 10,\n",
       " 'indication': 11,\n",
       " 'enzyme': 12,\n",
       " 'transporter': 13,\n",
       " 'off-label use': 14,\n",
       " 'linked to': 15,\n",
       " 'phenotype absent': 16,\n",
       " 'carrier': 17}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the relation type within data config of the BioBridge PrimeKG\n",
    "biobridge_data.get_data_config()['relation_type']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'biological_process': 768,\n",
       " 'cellular_component': 768,\n",
       " 'disease': 768,\n",
       " 'drug': 512,\n",
       " 'molecular_function': 768,\n",
       " 'gene/protein': 2560}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the embedding dimension within data config of the BioBridge PrimeKG\n",
    "# Note that, not all of node types have embeddings\n",
    "biobridge_data.get_data_config()['emb_dim']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check BioBridge-PrimeKG Node Information"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "BioBridge has provided us with node information for each modalities of PrimeKG.\n",
    "In particular, they included the information for the following modalities:\n",
    "- protein (sequence)\n",
    "- molecular function (texts)\n",
    "- cellular component (texts)\n",
    "- biological process (texts)\n",
    "- drug (SMILES strings)\n",
    "- disease (texts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['gene/protein', 'molecular_function', 'cellular_component', 'biological_process', 'drug', 'disease'])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the node information of the BioBridge PrimeKG\n",
    "biobridge_node_info = biobridge_data.get_node_info_dict()\n",
    "biobridge_node_info.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
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       "        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>node_index</th>\n",
       "      <th>node_id</th>\n",
       "      <th>node_type</th>\n",
       "      <th>node_name</th>\n",
       "      <th>node_source</th>\n",
       "      <th>sequence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>9796</td>\n",
       "      <td>gene/protein</td>\n",
       "      <td>PHYHIP</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>MELLSTPHSIEINNITCDSFRISWAMEDSDLERVTHYFIDLNKKEN...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>7918</td>\n",
       "      <td>gene/protein</td>\n",
       "      <td>GPANK1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>MSRPLLITFTPATDPSDLWKDGQQQPQPEKPESTLDGAAARAFYEA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>8233</td>\n",
       "      <td>gene/protein</td>\n",
       "      <td>ZRSR2</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>MAAPEKMTFPEKPSHKKYRAALKKEKRKKRRQELARLRDSGLSQKE...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4899</td>\n",
       "      <td>gene/protein</td>\n",
       "      <td>NRF1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>MEEHGVTQTEHMATIEAHAVAQQVQQVHVATYTEHSMLSADEDSPS...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5297</td>\n",
       "      <td>gene/protein</td>\n",
       "      <td>PI4KA</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>MAAAPARGGGGGGGGGGGCSGSGSSASRGFYFNTVLSLARSLAVQR...</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19157</th>\n",
       "      <td>83735</td>\n",
       "      <td>100133251</td>\n",
       "      <td>gene/protein</td>\n",
       "      <td>PRR23D2</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>MYGYRRLRSPRDSQTEPQNDNEGETSLATTQMNPPKRRQVEQGPST...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19158</th>\n",
       "      <td>83735</td>\n",
       "      <td>100133251</td>\n",
       "      <td>gene/protein</td>\n",
       "      <td>PRR23D2</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>MYGYRRLRSPRDSQTEPQNDNEGETSLATTQMNPPKRRQVEQGPST...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19159</th>\n",
       "      <td>83740</td>\n",
       "      <td>389649</td>\n",
       "      <td>gene/protein</td>\n",
       "      <td>C8orf86</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>MRPLGKGLLPAEELIRSNLGVGRSLRDCLSQSGKLAEELGSKRLKP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19160</th>\n",
       "      <td>83746</td>\n",
       "      <td>343990</td>\n",
       "      <td>gene/protein</td>\n",
       "      <td>CRACDL</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>MISTRVMDIKLREAAEGLGEDSTGKKKSKFKTFKKFFGKKKRKESP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19161</th>\n",
       "      <td>83747</td>\n",
       "      <td>340441</td>\n",
       "      <td>gene/protein</td>\n",
       "      <td>POTEA</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>MVAEVSPKLAASPMKKPFGFRGKMGKWCCCCFPCCRGSGKNNMGAW...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>19162 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       node_index    node_id     node_type node_name node_source  \\\n",
       "0               0       9796  gene/protein    PHYHIP        NCBI   \n",
       "1               1       7918  gene/protein    GPANK1        NCBI   \n",
       "2               2       8233  gene/protein     ZRSR2        NCBI   \n",
       "3               3       4899  gene/protein      NRF1        NCBI   \n",
       "4               4       5297  gene/protein     PI4KA        NCBI   \n",
       "...           ...        ...           ...       ...         ...   \n",
       "19157       83735  100133251  gene/protein   PRR23D2        NCBI   \n",
       "19158       83735  100133251  gene/protein   PRR23D2        NCBI   \n",
       "19159       83740     389649  gene/protein   C8orf86        NCBI   \n",
       "19160       83746     343990  gene/protein    CRACDL        NCBI   \n",
       "19161       83747     340441  gene/protein     POTEA        NCBI   \n",
       "\n",
       "                                                sequence  \n",
       "0      MELLSTPHSIEINNITCDSFRISWAMEDSDLERVTHYFIDLNKKEN...  \n",
       "1      MSRPLLITFTPATDPSDLWKDGQQQPQPEKPESTLDGAAARAFYEA...  \n",
       "2      MAAPEKMTFPEKPSHKKYRAALKKEKRKKRRQELARLRDSGLSQKE...  \n",
       "3      MEEHGVTQTEHMATIEAHAVAQQVQQVHVATYTEHSMLSADEDSPS...  \n",
       "4      MAAAPARGGGGGGGGGGGCSGSGSSASRGFYFNTVLSLARSLAVQR...  \n",
       "...                                                  ...  \n",
       "19157  MYGYRRLRSPRDSQTEPQNDNEGETSLATTQMNPPKRRQVEQGPST...  \n",
       "19158  MYGYRRLRSPRDSQTEPQNDNEGETSLATTQMNPPKRRQVEQGPST...  \n",
       "19159  MRPLGKGLLPAEELIRSNLGVGRSLRDCLSQSGKLAEELGSKRLKP...  \n",
       "19160  MISTRVMDIKLREAAEGLGEDSTGKKKSKFKTFKKFFGKKKRKESP...  \n",
       "19161  MVAEVSPKLAASPMKKPFGFRGKMGKWCCCCFPCCRGSGKNNMGAW...  \n",
       "\n",
       "[19162 rows x 6 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check a sample node information of gene/protein\n",
    "biobridge_node_info['gene/protein']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>node_index</th>\n",
       "      <th>node_id</th>\n",
       "      <th>node_type</th>\n",
       "      <th>node_name</th>\n",
       "      <th>node_source</th>\n",
       "      <th>description</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>53517</td>\n",
       "      <td>8168</td>\n",
       "      <td>molecular_function</td>\n",
       "      <td>methyltransferase activity</td>\n",
       "      <td>GO</td>\n",
       "      <td>Catalysis of the transfer of a methyl group to...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>53518</td>\n",
       "      <td>140101</td>\n",
       "      <td>molecular_function</td>\n",
       "      <td>catalytic activity, acting on a tRNA</td>\n",
       "      <td>GO</td>\n",
       "      <td>Catalytic activity that acts to modify a tRNA.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>53519</td>\n",
       "      <td>140097</td>\n",
       "      <td>molecular_function</td>\n",
       "      <td>catalytic activity, acting on DNA</td>\n",
       "      <td>GO</td>\n",
       "      <td>Catalytic activity that acts to modify DNA.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>53520</td>\n",
       "      <td>140096</td>\n",
       "      <td>molecular_function</td>\n",
       "      <td>catalytic activity, acting on a protein</td>\n",
       "      <td>GO</td>\n",
       "      <td>Catalytic activity that acts to modify a protein.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>53521</td>\n",
       "      <td>140098</td>\n",
       "      <td>molecular_function</td>\n",
       "      <td>catalytic activity, acting on RNA</td>\n",
       "      <td>GO</td>\n",
       "      <td>Catalytic activity that acts to modify RNA, dr...</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10961</th>\n",
       "      <td>124216</td>\n",
       "      <td>42880</td>\n",
       "      <td>molecular_function</td>\n",
       "      <td>D-glucuronate transmembrane transporter activity</td>\n",
       "      <td>GO</td>\n",
       "      <td>Enables the transfer of D-glucuronate, the D-e...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10962</th>\n",
       "      <td>124217</td>\n",
       "      <td>61922</td>\n",
       "      <td>molecular_function</td>\n",
       "      <td>histone propionyltransferase activity</td>\n",
       "      <td>GO</td>\n",
       "      <td>Catalysis of the reaction: propionyl-CoA + his...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10963</th>\n",
       "      <td>124218</td>\n",
       "      <td>61995</td>\n",
       "      <td>molecular_function</td>\n",
       "      <td>ATP-dependent protein-DNA complex displacement...</td>\n",
       "      <td>GO</td>\n",
       "      <td>An activity that displaces proteins or protein...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10964</th>\n",
       "      <td>124219</td>\n",
       "      <td>51266</td>\n",
       "      <td>molecular_function</td>\n",
       "      <td>sirohydrochlorin ferrochelatase activity</td>\n",
       "      <td>GO</td>\n",
       "      <td>Catalysis of the reaction: siroheme + 2 H+ = F...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10965</th>\n",
       "      <td>124220</td>\n",
       "      <td>51740</td>\n",
       "      <td>molecular_function</td>\n",
       "      <td>ethylene binding</td>\n",
       "      <td>GO</td>\n",
       "      <td>Binding to ethylene (C2-H4, ethene), a simple ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10966 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       node_index  node_id           node_type  \\\n",
       "0           53517     8168  molecular_function   \n",
       "1           53518   140101  molecular_function   \n",
       "2           53519   140097  molecular_function   \n",
       "3           53520   140096  molecular_function   \n",
       "4           53521   140098  molecular_function   \n",
       "...           ...      ...                 ...   \n",
       "10961      124216    42880  molecular_function   \n",
       "10962      124217    61922  molecular_function   \n",
       "10963      124218    61995  molecular_function   \n",
       "10964      124219    51266  molecular_function   \n",
       "10965      124220    51740  molecular_function   \n",
       "\n",
       "                                               node_name node_source  \\\n",
       "0                             methyltransferase activity          GO   \n",
       "1                   catalytic activity, acting on a tRNA          GO   \n",
       "2                      catalytic activity, acting on DNA          GO   \n",
       "3                catalytic activity, acting on a protein          GO   \n",
       "4                      catalytic activity, acting on RNA          GO   \n",
       "...                                                  ...         ...   \n",
       "10961   D-glucuronate transmembrane transporter activity          GO   \n",
       "10962              histone propionyltransferase activity          GO   \n",
       "10963  ATP-dependent protein-DNA complex displacement...          GO   \n",
       "10964           sirohydrochlorin ferrochelatase activity          GO   \n",
       "10965                                   ethylene binding          GO   \n",
       "\n",
       "                                             description  \n",
       "0      Catalysis of the transfer of a methyl group to...  \n",
       "1         Catalytic activity that acts to modify a tRNA.  \n",
       "2            Catalytic activity that acts to modify DNA.  \n",
       "3      Catalytic activity that acts to modify a protein.  \n",
       "4      Catalytic activity that acts to modify RNA, dr...  \n",
       "...                                                  ...  \n",
       "10961  Enables the transfer of D-glucuronate, the D-e...  \n",
       "10962  Catalysis of the reaction: propionyl-CoA + his...  \n",
       "10963  An activity that displaces proteins or protein...  \n",
       "10964  Catalysis of the reaction: siroheme + 2 H+ = F...  \n",
       "10965  Binding to ethylene (C2-H4, ethene), a simple ...  \n",
       "\n",
       "[10966 rows x 6 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check a sample node information of molecular_function\n",
    "biobridge_node_info['molecular_function']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>55515</td>\n",
       "      <td>110165</td>\n",
       "      <td>cellular_component</td>\n",
       "      <td>cellular anatomical entity</td>\n",
       "      <td>GO</td>\n",
       "      <td>A part of a cellular organism that is either a...</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>55516</td>\n",
       "      <td>30137</td>\n",
       "      <td>cellular_component</td>\n",
       "      <td>COPI-coated vesicle</td>\n",
       "      <td>GO</td>\n",
       "      <td>A vesicle with a coat formed of the COPI coat ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>55517</td>\n",
       "      <td>30133</td>\n",
       "      <td>cellular_component</td>\n",
       "      <td>transport vesicle</td>\n",
       "      <td>GO</td>\n",
       "      <td>Any of the vesicles of the constitutive secret...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>55520</td>\n",
       "      <td>5777</td>\n",
       "      <td>cellular_component</td>\n",
       "      <td>peroxisome</td>\n",
       "      <td>GO</td>\n",
       "      <td>A small organelle enclosed by a single membran...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>55524</td>\n",
       "      <td>99512</td>\n",
       "      <td>cellular_component</td>\n",
       "      <td>supramolecular fiber</td>\n",
       "      <td>GO</td>\n",
       "      <td>A polymer consisting of an indefinite number o...</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4008</th>\n",
       "      <td>127430</td>\n",
       "      <td>44169</td>\n",
       "      <td>cellular_component</td>\n",
       "      <td>host cell rough endoplasmic reticulum membrane</td>\n",
       "      <td>GO</td>\n",
       "      <td>The lipid bilayer surrounding the host cell ro...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4009</th>\n",
       "      <td>127431</td>\n",
       "      <td>98652</td>\n",
       "      <td>cellular_component</td>\n",
       "      <td>collagen type VII anchoring fibril</td>\n",
       "      <td>GO</td>\n",
       "      <td>An antiparallel dimer of two collagen VII trim...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4010</th>\n",
       "      <td>127432</td>\n",
       "      <td>90732</td>\n",
       "      <td>cellular_component</td>\n",
       "      <td>cofilin-actin rod</td>\n",
       "      <td>GO</td>\n",
       "      <td>A cellular structure consisting of parallel, h...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4011</th>\n",
       "      <td>127433</td>\n",
       "      <td>779</td>\n",
       "      <td>cellular_component</td>\n",
       "      <td>condensed chromosome, centromeric region</td>\n",
       "      <td>GO</td>\n",
       "      <td>The region of a condensed chromosome that incl...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4012</th>\n",
       "      <td>127434</td>\n",
       "      <td>32282</td>\n",
       "      <td>cellular_component</td>\n",
       "      <td>plastid acetyl-CoA carboxylase complex</td>\n",
       "      <td>GO</td>\n",
       "      <td>An acetyl-CoA carboxylase complex located in t...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4013 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      node_index  node_id           node_type  \\\n",
       "0          55515   110165  cellular_component   \n",
       "1          55516    30137  cellular_component   \n",
       "2          55517    30133  cellular_component   \n",
       "3          55520     5777  cellular_component   \n",
       "4          55524    99512  cellular_component   \n",
       "...          ...      ...                 ...   \n",
       "4008      127430    44169  cellular_component   \n",
       "4009      127431    98652  cellular_component   \n",
       "4010      127432    90732  cellular_component   \n",
       "4011      127433      779  cellular_component   \n",
       "4012      127434    32282  cellular_component   \n",
       "\n",
       "                                           node_name node_source  \\\n",
       "0                         cellular anatomical entity          GO   \n",
       "1                                COPI-coated vesicle          GO   \n",
       "2                                  transport vesicle          GO   \n",
       "3                                         peroxisome          GO   \n",
       "4                               supramolecular fiber          GO   \n",
       "...                                              ...         ...   \n",
       "4008  host cell rough endoplasmic reticulum membrane          GO   \n",
       "4009              collagen type VII anchoring fibril          GO   \n",
       "4010                               cofilin-actin rod          GO   \n",
       "4011        condensed chromosome, centromeric region          GO   \n",
       "4012          plastid acetyl-CoA carboxylase complex          GO   \n",
       "\n",
       "                                            description  \n",
       "0     A part of a cellular organism that is either a...  \n",
       "1     A vesicle with a coat formed of the COPI coat ...  \n",
       "2     Any of the vesicles of the constitutive secret...  \n",
       "3     A small organelle enclosed by a single membran...  \n",
       "4     A polymer consisting of an indefinite number o...  \n",
       "...                                                 ...  \n",
       "4008  The lipid bilayer surrounding the host cell ro...  \n",
       "4009  An antiparallel dimer of two collagen VII trim...  \n",
       "4010  A cellular structure consisting of parallel, h...  \n",
       "4011  The region of a condensed chromosome that incl...  \n",
       "4012  An acetyl-CoA carboxylase complex located in t...  \n",
       "\n",
       "[4013 rows x 6 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check a sample node information of cellular_component\n",
    "biobridge_node_info['cellular_component']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>node_index</th>\n",
       "      <th>node_id</th>\n",
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       "      <th>0</th>\n",
       "      <td>39898</td>\n",
       "      <td>51581</td>\n",
       "      <td>biological_process</td>\n",
       "      <td>negative regulation of neurotransmitter uptake</td>\n",
       "      <td>GO</td>\n",
       "      <td>Any process that stops, prevents, or reduces t...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>39899</td>\n",
       "      <td>43271</td>\n",
       "      <td>biological_process</td>\n",
       "      <td>negative regulation of ion transport</td>\n",
       "      <td>GO</td>\n",
       "      <td>Any process that stops, prevents, or reduces t...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>39900</td>\n",
       "      <td>51611</td>\n",
       "      <td>biological_process</td>\n",
       "      <td>regulation of serotonin uptake</td>\n",
       "      <td>GO</td>\n",
       "      <td>Any process that modulates the frequency, rate...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>39901</td>\n",
       "      <td>51616</td>\n",
       "      <td>biological_process</td>\n",
       "      <td>regulation of histamine uptake</td>\n",
       "      <td>GO</td>\n",
       "      <td>Any process that modulates the frequency, rate...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>39902</td>\n",
       "      <td>51956</td>\n",
       "      <td>biological_process</td>\n",
       "      <td>negative regulation of amino acid transport</td>\n",
       "      <td>GO</td>\n",
       "      <td>Any process that stops, prevents, or reduces t...</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27473</th>\n",
       "      <td>115046</td>\n",
       "      <td>60654</td>\n",
       "      <td>biological_process</td>\n",
       "      <td>mammary gland cord elongation</td>\n",
       "      <td>GO</td>\n",
       "      <td>The process in which the mammary gland sprout ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27474</th>\n",
       "      <td>115047</td>\n",
       "      <td>1903696</td>\n",
       "      <td>biological_process</td>\n",
       "      <td>protein localization to horsetail-astral micro...</td>\n",
       "      <td>GO</td>\n",
       "      <td>A process in which a protein is transported to...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27475</th>\n",
       "      <td>115048</td>\n",
       "      <td>3372</td>\n",
       "      <td>biological_process</td>\n",
       "      <td>establishment or maintenance of cytoskeleton p...</td>\n",
       "      <td>GO</td>\n",
       "      <td>Any cellular process that results in the speci...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27476</th>\n",
       "      <td>115049</td>\n",
       "      <td>97624</td>\n",
       "      <td>biological_process</td>\n",
       "      <td>UDP-galactose transmembrane import into Golgi ...</td>\n",
       "      <td>GO</td>\n",
       "      <td>The directed movement of UDP-galactose into th...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27477</th>\n",
       "      <td>115050</td>\n",
       "      <td>48072</td>\n",
       "      <td>biological_process</td>\n",
       "      <td>compound eye pigmentation</td>\n",
       "      <td>GO</td>\n",
       "      <td>Establishment of a pattern of pigment in the c...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>27478 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       node_index  node_id           node_type  \\\n",
       "0           39898    51581  biological_process   \n",
       "1           39899    43271  biological_process   \n",
       "2           39900    51611  biological_process   \n",
       "3           39901    51616  biological_process   \n",
       "4           39902    51956  biological_process   \n",
       "...           ...      ...                 ...   \n",
       "27473      115046    60654  biological_process   \n",
       "27474      115047  1903696  biological_process   \n",
       "27475      115048     3372  biological_process   \n",
       "27476      115049    97624  biological_process   \n",
       "27477      115050    48072  biological_process   \n",
       "\n",
       "                                               node_name node_source  \\\n",
       "0         negative regulation of neurotransmitter uptake          GO   \n",
       "1                   negative regulation of ion transport          GO   \n",
       "2                         regulation of serotonin uptake          GO   \n",
       "3                         regulation of histamine uptake          GO   \n",
       "4            negative regulation of amino acid transport          GO   \n",
       "...                                                  ...         ...   \n",
       "27473                      mammary gland cord elongation          GO   \n",
       "27474  protein localization to horsetail-astral micro...          GO   \n",
       "27475  establishment or maintenance of cytoskeleton p...          GO   \n",
       "27476  UDP-galactose transmembrane import into Golgi ...          GO   \n",
       "27477                          compound eye pigmentation          GO   \n",
       "\n",
       "                                             description  \n",
       "0      Any process that stops, prevents, or reduces t...  \n",
       "1      Any process that stops, prevents, or reduces t...  \n",
       "2      Any process that modulates the frequency, rate...  \n",
       "3      Any process that modulates the frequency, rate...  \n",
       "4      Any process that stops, prevents, or reduces t...  \n",
       "...                                                  ...  \n",
       "27473  The process in which the mammary gland sprout ...  \n",
       "27474  A process in which a protein is transported to...  \n",
       "27475  Any cellular process that results in the speci...  \n",
       "27476  The directed movement of UDP-galactose into th...  \n",
       "27477  Establishment of a pattern of pigment in the c...  \n",
       "\n",
       "[27478 rows x 6 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check a sample node information of biological_process\n",
    "biobridge_node_info['biological_process']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>node_index</th>\n",
       "      <th>description</th>\n",
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       "      <th>pharmacodynamics</th>\n",
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       "      <th>atc_2</th>\n",
       "      <th>...</th>\n",
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       "      <th>node_source</th>\n",
       "      <th>name</th>\n",
       "      <th>smiles</th>\n",
       "      <th>logP ALOGPS</th>\n",
       "      <th>logP ChemAxon</th>\n",
       "      <th>solubility ALOGPS</th>\n",
       "      <th>pKa (strongest acidic)</th>\n",
       "      <th>pKa (strongest basic)</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14014</td>\n",
       "      <td>Flunisolide (marketed as AeroBid, Nasalide, Na...</td>\n",
       "      <td>The half-life is 1.8 hours</td>\n",
       "      <td>For the maintenance treatment of asthma as a p...</td>\n",
       "      <td>Flunisolide is a glucocorticoid receptor agoni...</td>\n",
       "      <td>Approximately 40% after oral inhalation</td>\n",
       "      <td>Flunisolide is a synthetic corticosteroid. It ...</td>\n",
       "      <td>Flunisolide is a solid.</td>\n",
       "      <td>Flunisolide is anatomically related to respira...</td>\n",
       "      <td>Flunisolide is in the therapeutic group of nas...</td>\n",
       "      <td>...</td>\n",
       "      <td>drug</td>\n",
       "      <td>Flunisolide</td>\n",
       "      <td>DrugBank</td>\n",
       "      <td>Flunisolide</td>\n",
       "      <td>[H][C@@]12C[C@@]3([H])[C@]4([H])C[C@H](F)C5=CC...</td>\n",
       "      <td>2.20</td>\n",
       "      <td>1.56</td>\n",
       "      <td>3.74e-02 g/l</td>\n",
       "      <td>13.73</td>\n",
       "      <td>-2.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>14015</td>\n",
       "      <td>Alclometasone is synthetic glucocorticoid ster...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>For the relief of the inflammatory and pruriti...</td>\n",
       "      <td>The mechanism of the anti-inflammatory activit...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alclometasone is a synthetic corticosteroid fo...</td>\n",
       "      <td>Alclometasone is a solid.</td>\n",
       "      <td>Alclometasone is anatomically related to derma...</td>\n",
       "      <td>Alclometasone is in the therapeutic group of c...</td>\n",
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       "      <td>2.11</td>\n",
       "      <td>1.68</td>\n",
       "      <td>1.37e-01 g/l</td>\n",
       "      <td>12.45</td>\n",
       "      <td>-2.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14016</td>\n",
       "      <td>Medrysone is a corticosteroid used in ophthalm...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>For the treatment of allergic conjunctivitis, ...</td>\n",
       "      <td>There is no generally accepted explanation for...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Medrysone is a topical anti-inflammatory corti...</td>\n",
       "      <td>Medrysone is a solid.</td>\n",
       "      <td>Medrysone is anatomically related to sensory o...</td>\n",
       "      <td>Medrysone is in the therapeutic group of ophth...</td>\n",
       "      <td>...</td>\n",
       "      <td>drug</td>\n",
       "      <td>Medrysone</td>\n",
       "      <td>DrugBank</td>\n",
       "      <td>Medrysone</td>\n",
       "      <td>[H][C@@]12CC[C@H](C(C)=O)[C@@]1(C)C[C@H](O)[C@...</td>\n",
       "      <td>3.06</td>\n",
       "      <td>3.13</td>\n",
       "      <td>3.37e-02 g/l</td>\n",
       "      <td>19.14</td>\n",
       "      <td>-0.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14017</td>\n",
       "      <td>A glucocorticoid employed, usually as eye drop...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>For the ophthalmic treatment of corticosteroid...</td>\n",
       "      <td>There is no generally accepted explanation for...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Corticosteroids such as fluorometholone inhibi...</td>\n",
       "      <td>Fluorometholone is a solid.</td>\n",
       "      <td>Fluorometholone is anatomically related to der...</td>\n",
       "      <td>Fluorometholone is in the therapeutic group of...</td>\n",
       "      <td>...</td>\n",
       "      <td>drug</td>\n",
       "      <td>Fluorometholone</td>\n",
       "      <td>DrugBank</td>\n",
       "      <td>Fluorometholone</td>\n",
       "      <td>[H][C@@]12CC[C@](O)(C(C)=O)[C@@]1(C)C[C@H](O)[...</td>\n",
       "      <td>2.34</td>\n",
       "      <td>2.42</td>\n",
       "      <td>1.66e-02 g/l</td>\n",
       "      <td>12.65</td>\n",
       "      <td>-3.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14018</td>\n",
       "      <td>Beclomethasone dipropionate is a second-genera...</td>\n",
       "      <td>Following intravenous administration, the half...</td>\n",
       "      <td>Indicated for oral inhalation use in the maint...</td>\n",
       "      <td>Beclomethasone dipropionate is a corticosteroi...</td>\n",
       "      <td>Based on the findings of _in vitro_ studies, t...</td>\n",
       "      <td>Inflammatory conditions, including asthma, der...</td>\n",
       "      <td>Beclomethasone dipropionate is a solid.</td>\n",
       "      <td>Beclomethasone dipropionate is anatomically re...</td>\n",
       "      <td>Beclomethasone dipropionate is in the therapeu...</td>\n",
       "      <td>...</td>\n",
       "      <td>drug</td>\n",
       "      <td>Beclomethasone dipropionate</td>\n",
       "      <td>DrugBank</td>\n",
       "      <td>Beclomethasone dipropionate</td>\n",
       "      <td>[H][C@@]12C[C@H](C)[C@](OC(=O)CC)(C(=O)COC(=O)...</td>\n",
       "      <td>3.69</td>\n",
       "      <td>4.43</td>\n",
       "      <td>2.08e-03 g/l</td>\n",
       "      <td>13.85</td>\n",
       "      <td>-3.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>6943</th>\n",
       "      <td>21955</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Metabutethamine is anatomically related to ner...</td>\n",
       "      <td>Metabutethamine is in the therapeutic group of...</td>\n",
       "      <td>...</td>\n",
       "      <td>drug</td>\n",
       "      <td>Metabutethamine</td>\n",
       "      <td>DrugBank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CC(C)CNCCOC(=O)C1=CC=CC(N)=C1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6944</th>\n",
       "      <td>21956</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Quinisocaine is anatomically related to dermat...</td>\n",
       "      <td>Quinisocaine is in the therapeutic group of an...</td>\n",
       "      <td>...</td>\n",
       "      <td>drug</td>\n",
       "      <td>Quinisocaine</td>\n",
       "      <td>DrugBank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CCCCC1=CC2=CC=CC=C2C(OCCN(C)C)=N1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6945</th>\n",
       "      <td>39888</td>\n",
       "      <td>Benzyl benzoate is one of the older preparatio...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Used to kill lice and the mites responsible fo...</td>\n",
       "      <td>Benzyl benzoate exerts toxic effects on the ne...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Benzyl benzoate is one of the older preparatio...</td>\n",
       "      <td>Benzyl benzoate is a liquid.</td>\n",
       "      <td>Benzyl benzoate is anatomically related to ant...</td>\n",
       "      <td>Benzyl benzoate is in the therapeutic group of...</td>\n",
       "      <td>...</td>\n",
       "      <td>drug</td>\n",
       "      <td>Benzyl benzoate</td>\n",
       "      <td>DrugBank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>O=C(OCC1=CC=CC=C1)C1=CC=CC=C1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6946</th>\n",
       "      <td>39894</td>\n",
       "      <td>Sulfur hexafluoride is an ultrasound contrast ...</td>\n",
       "      <td>The terminal half-life of SF6 in blood was app...</td>\n",
       "      <td>Echocardiography: Sulfur hexafluoride is indic...</td>\n",
       "      <td>Within the blood, the acoustic impedance of Lu...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sulfur hexafluoride provides useful echocardio...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sulfur hexafluoride is anatomically related to...</td>\n",
       "      <td>Sulfur hexafluoride is in the therapeutic grou...</td>\n",
       "      <td>...</td>\n",
       "      <td>drug</td>\n",
       "      <td>Sulfur hexafluoride</td>\n",
       "      <td>DrugBank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FS(F)(F)(F)(F)F</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6947</th>\n",
       "      <td>39895</td>\n",
       "      <td>Butoconazole is an imidazole antifungal used i...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>For the local treatment of vulvovaginal candid...</td>\n",
       "      <td>The exact mechanism of the antifungal action o...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Butoconazole is an imidazole derivative that h...</td>\n",
       "      <td>Butoconazole is a solid.</td>\n",
       "      <td>Butoconazole is anatomically related to genito...</td>\n",
       "      <td>Butoconazole is in the therapeutic group of gy...</td>\n",
       "      <td>...</td>\n",
       "      <td>drug</td>\n",
       "      <td>Butoconazole</td>\n",
       "      <td>DrugBank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ClC1=CC=C(CCC(CN2C=CN=C2)SC2=C(Cl)C=CC=C2Cl)C=C1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6948 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      node_index                                        description  \\\n",
       "0          14014  Flunisolide (marketed as AeroBid, Nasalide, Na...   \n",
       "1          14015  Alclometasone is synthetic glucocorticoid ster...   \n",
       "2          14016  Medrysone is a corticosteroid used in ophthalm...   \n",
       "3          14017  A glucocorticoid employed, usually as eye drop...   \n",
       "4          14018  Beclomethasone dipropionate is a second-genera...   \n",
       "...          ...                                                ...   \n",
       "6943       21955                                                NaN   \n",
       "6944       21956                                                NaN   \n",
       "6945       39888  Benzyl benzoate is one of the older preparatio...   \n",
       "6946       39894  Sulfur hexafluoride is an ultrasound contrast ...   \n",
       "6947       39895  Butoconazole is an imidazole antifungal used i...   \n",
       "\n",
       "                                              half_life  \\\n",
       "0                            The half-life is 1.8 hours   \n",
       "1                                                   NaN   \n",
       "2                                                   NaN   \n",
       "3                                                   NaN   \n",
       "4     Following intravenous administration, the half...   \n",
       "...                                                 ...   \n",
       "6943                                                NaN   \n",
       "6944                                                NaN   \n",
       "6945                                                NaN   \n",
       "6946  The terminal half-life of SF6 in blood was app...   \n",
       "6947                                                NaN   \n",
       "\n",
       "                                             indication  \\\n",
       "0     For the maintenance treatment of asthma as a p...   \n",
       "1     For the relief of the inflammatory and pruriti...   \n",
       "2     For the treatment of allergic conjunctivitis, ...   \n",
       "3     For the ophthalmic treatment of corticosteroid...   \n",
       "4     Indicated for oral inhalation use in the maint...   \n",
       "...                                                 ...   \n",
       "6943                                                NaN   \n",
       "6944                                                NaN   \n",
       "6945  Used to kill lice and the mites responsible fo...   \n",
       "6946  Echocardiography: Sulfur hexafluoride is indic...   \n",
       "6947  For the local treatment of vulvovaginal candid...   \n",
       "\n",
       "                                    mechanism_of_action  \\\n",
       "0     Flunisolide is a glucocorticoid receptor agoni...   \n",
       "1     The mechanism of the anti-inflammatory activit...   \n",
       "2     There is no generally accepted explanation for...   \n",
       "3     There is no generally accepted explanation for...   \n",
       "4     Beclomethasone dipropionate is a corticosteroi...   \n",
       "...                                                 ...   \n",
       "6943                                                NaN   \n",
       "6944                                                NaN   \n",
       "6945  Benzyl benzoate exerts toxic effects on the ne...   \n",
       "6946  Within the blood, the acoustic impedance of Lu...   \n",
       "6947  The exact mechanism of the antifungal action o...   \n",
       "\n",
       "                                        protein_binding  \\\n",
       "0               Approximately 40% after oral inhalation   \n",
       "1                                                   NaN   \n",
       "2                                                   NaN   \n",
       "3                                                   NaN   \n",
       "4     Based on the findings of _in vitro_ studies, t...   \n",
       "...                                                 ...   \n",
       "6943                                                NaN   \n",
       "6944                                                NaN   \n",
       "6945                                                NaN   \n",
       "6946                                                NaN   \n",
       "6947                                                NaN   \n",
       "\n",
       "                                       pharmacodynamics  \\\n",
       "0     Flunisolide is a synthetic corticosteroid. It ...   \n",
       "1     Alclometasone is a synthetic corticosteroid fo...   \n",
       "2     Medrysone is a topical anti-inflammatory corti...   \n",
       "3     Corticosteroids such as fluorometholone inhibi...   \n",
       "4     Inflammatory conditions, including asthma, der...   \n",
       "...                                                 ...   \n",
       "6943                                                NaN   \n",
       "6944                                                NaN   \n",
       "6945  Benzyl benzoate is one of the older preparatio...   \n",
       "6946  Sulfur hexafluoride provides useful echocardio...   \n",
       "6947  Butoconazole is an imidazole derivative that h...   \n",
       "\n",
       "                                        state  \\\n",
       "0                     Flunisolide is a solid.   \n",
       "1                   Alclometasone is a solid.   \n",
       "2                       Medrysone is a solid.   \n",
       "3                 Fluorometholone is a solid.   \n",
       "4     Beclomethasone dipropionate is a solid.   \n",
       "...                                       ...   \n",
       "6943                                      NaN   \n",
       "6944                                      NaN   \n",
       "6945             Benzyl benzoate is a liquid.   \n",
       "6946                                      NaN   \n",
       "6947                 Butoconazole is a solid.   \n",
       "\n",
       "                                                  atc_1  \\\n",
       "0     Flunisolide is anatomically related to respira...   \n",
       "1     Alclometasone is anatomically related to derma...   \n",
       "2     Medrysone is anatomically related to sensory o...   \n",
       "3     Fluorometholone is anatomically related to der...   \n",
       "4     Beclomethasone dipropionate is anatomically re...   \n",
       "...                                                 ...   \n",
       "6943  Metabutethamine is anatomically related to ner...   \n",
       "6944  Quinisocaine is anatomically related to dermat...   \n",
       "6945  Benzyl benzoate is anatomically related to ant...   \n",
       "6946  Sulfur hexafluoride is anatomically related to...   \n",
       "6947  Butoconazole is anatomically related to genito...   \n",
       "\n",
       "                                                  atc_2  ... node_type  \\\n",
       "0     Flunisolide is in the therapeutic group of nas...  ...      drug   \n",
       "1     Alclometasone is in the therapeutic group of c...  ...      drug   \n",
       "2     Medrysone is in the therapeutic group of ophth...  ...      drug   \n",
       "3     Fluorometholone is in the therapeutic group of...  ...      drug   \n",
       "4     Beclomethasone dipropionate is in the therapeu...  ...      drug   \n",
       "...                                                 ...  ...       ...   \n",
       "6943  Metabutethamine is in the therapeutic group of...  ...      drug   \n",
       "6944  Quinisocaine is in the therapeutic group of an...  ...      drug   \n",
       "6945  Benzyl benzoate is in the therapeutic group of...  ...      drug   \n",
       "6946  Sulfur hexafluoride is in the therapeutic grou...  ...      drug   \n",
       "6947  Butoconazole is in the therapeutic group of gy...  ...      drug   \n",
       "\n",
       "                        node_name node_source                         name  \\\n",
       "0                     Flunisolide    DrugBank                  Flunisolide   \n",
       "1                   Alclometasone    DrugBank                Alclometasone   \n",
       "2                       Medrysone    DrugBank                    Medrysone   \n",
       "3                 Fluorometholone    DrugBank              Fluorometholone   \n",
       "4     Beclomethasone dipropionate    DrugBank  Beclomethasone dipropionate   \n",
       "...                           ...         ...                          ...   \n",
       "6943              Metabutethamine    DrugBank                          NaN   \n",
       "6944                 Quinisocaine    DrugBank                          NaN   \n",
       "6945              Benzyl benzoate    DrugBank                          NaN   \n",
       "6946          Sulfur hexafluoride    DrugBank                          NaN   \n",
       "6947                 Butoconazole    DrugBank                          NaN   \n",
       "\n",
       "                                                 smiles logP ALOGPS  \\\n",
       "0     [H][C@@]12C[C@@]3([H])[C@]4([H])C[C@H](F)C5=CC...        2.20   \n",
       "1     [H][C@@]12C[C@@H](C)[C@](O)(C(=O)CO)[C@@]1(C)C...        2.11   \n",
       "2     [H][C@@]12CC[C@H](C(C)=O)[C@@]1(C)C[C@H](O)[C@...        3.06   \n",
       "3     [H][C@@]12CC[C@](O)(C(C)=O)[C@@]1(C)C[C@H](O)[...        2.34   \n",
       "4     [H][C@@]12C[C@H](C)[C@](OC(=O)CC)(C(=O)COC(=O)...        3.69   \n",
       "...                                                 ...         ...   \n",
       "6943                      CC(C)CNCCOC(=O)C1=CC=CC(N)=C1         NaN   \n",
       "6944                  CCCCC1=CC2=CC=CC=C2C(OCCN(C)C)=N1         NaN   \n",
       "6945                      O=C(OCC1=CC=CC=C1)C1=CC=CC=C1         NaN   \n",
       "6946                                    FS(F)(F)(F)(F)F         NaN   \n",
       "6947   ClC1=CC=C(CCC(CN2C=CN=C2)SC2=C(Cl)C=CC=C2Cl)C=C1         NaN   \n",
       "\n",
       "     logP ChemAxon solubility ALOGPS pKa (strongest acidic)  \\\n",
       "0             1.56      3.74e-02 g/l                  13.73   \n",
       "1             1.68      1.37e-01 g/l                  12.45   \n",
       "2             3.13      3.37e-02 g/l                  19.14   \n",
       "3             2.42      1.66e-02 g/l                  12.65   \n",
       "4             4.43      2.08e-03 g/l                  13.85   \n",
       "...            ...               ...                    ...   \n",
       "6943           NaN               NaN                    NaN   \n",
       "6944           NaN               NaN                    NaN   \n",
       "6945           NaN               NaN                    NaN   \n",
       "6946           NaN               NaN                    NaN   \n",
       "6947           NaN               NaN                    NaN   \n",
       "\n",
       "     pKa (strongest basic)  \n",
       "0                    -2.90  \n",
       "1                    -2.90  \n",
       "2                    -0.26  \n",
       "3                    -3.40  \n",
       "4                    -3.30  \n",
       "...                    ...  \n",
       "6943                   NaN  \n",
       "6944                   NaN  \n",
       "6945                   NaN  \n",
       "6946                   NaN  \n",
       "6947                   NaN  \n",
       "\n",
       "[6948 rows x 29 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check a sample node information of drug\n",
    "biobridge_node_info['drug']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>node_index</th>\n",
       "      <th>mondo_id</th>\n",
       "      <th>mondo_name</th>\n",
       "      <th>definition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>27165</td>\n",
       "      <td>8019</td>\n",
       "      <td>mullerian aplasia and hyperandrogenism</td>\n",
       "      <td>Deficiency of the glycoprotein WNT4, associate...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>27165</td>\n",
       "      <td>8019</td>\n",
       "      <td>mullerian aplasia and hyperandrogenism</td>\n",
       "      <td>Deficiency of the glycoprotein WNT4, associate...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>27166</td>\n",
       "      <td>11043</td>\n",
       "      <td>myelodysplasia, immunodeficiency, facial dysmo...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>27168</td>\n",
       "      <td>8878</td>\n",
       "      <td>bone dysplasia, lethal Holmgren type</td>\n",
       "      <td>Bone dysplasia lethal Holmgren type (BDLH) is ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>27169</td>\n",
       "      <td>8905</td>\n",
       "      <td>predisposition to invasive fungal disease due ...</td>\n",
       "      <td>A rare, genetic primary immunodeficiency chara...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44128</th>\n",
       "      <td>99866</td>\n",
       "      <td>44144</td>\n",
       "      <td>panic disorder with agoraphobia</td>\n",
       "      <td>A disorder in which an individual experiences ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44129</th>\n",
       "      <td>99916</td>\n",
       "      <td>44797</td>\n",
       "      <td>desmoplastic nevus</td>\n",
       "      <td>A benign melanocytic nevus characterized by th...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44130</th>\n",
       "      <td>99916</td>\n",
       "      <td>44800</td>\n",
       "      <td>desmoplastic spitz nevus</td>\n",
       "      <td>A Spitz nevus associated with fibrous stroma f...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44131</th>\n",
       "      <td>99969</td>\n",
       "      <td>100023</td>\n",
       "      <td>self-limited familial and non-familial neonata...</td>\n",
       "      <td>A neonatal/infantile epilepsy sndrome that is ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44132</th>\n",
       "      <td>99969</td>\n",
       "      <td>100024</td>\n",
       "      <td>self-limited familial and non-familial infanti...</td>\n",
       "      <td>This syndrome is characterized by the onset of...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>44133 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       node_index  mondo_id  \\\n",
       "0           27165      8019   \n",
       "1           27165      8019   \n",
       "2           27166     11043   \n",
       "3           27168      8878   \n",
       "4           27169      8905   \n",
       "...           ...       ...   \n",
       "44128       99866     44144   \n",
       "44129       99916     44797   \n",
       "44130       99916     44800   \n",
       "44131       99969    100023   \n",
       "44132       99969    100024   \n",
       "\n",
       "                                              mondo_name  \\\n",
       "0                 mullerian aplasia and hyperandrogenism   \n",
       "1                 mullerian aplasia and hyperandrogenism   \n",
       "2      myelodysplasia, immunodeficiency, facial dysmo...   \n",
       "3                   bone dysplasia, lethal Holmgren type   \n",
       "4      predisposition to invasive fungal disease due ...   \n",
       "...                                                  ...   \n",
       "44128                    panic disorder with agoraphobia   \n",
       "44129                                 desmoplastic nevus   \n",
       "44130                           desmoplastic spitz nevus   \n",
       "44131  self-limited familial and non-familial neonata...   \n",
       "44132  self-limited familial and non-familial infanti...   \n",
       "\n",
       "                                              definition  \n",
       "0      Deficiency of the glycoprotein WNT4, associate...  \n",
       "1      Deficiency of the glycoprotein WNT4, associate...  \n",
       "2                                                    NaN  \n",
       "3      Bone dysplasia lethal Holmgren type (BDLH) is ...  \n",
       "4      A rare, genetic primary immunodeficiency chara...  \n",
       "...                                                  ...  \n",
       "44128  A disorder in which an individual experiences ...  \n",
       "44129  A benign melanocytic nevus characterized by th...  \n",
       "44130  A Spitz nevus associated with fibrous stroma f...  \n",
       "44131  A neonatal/infantile epilepsy sndrome that is ...  \n",
       "44132  This syndrome is characterized by the onset of...  \n",
       "\n",
       "[44133 rows x 4 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check a sample node information of disease\n",
    "biobridge_node_info['disease']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check BioBridge-PrimeKG Node Embeddings (Pre-Loaded)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "BioBridge provides a dictionary of pre-loaded embeddings, which can be obtained as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.04029838368296623,\n",
       " -0.018344514071941376,\n",
       " 0.02762659639120102,\n",
       " -0.026468712836503983,\n",
       " 0.021834833547472954,\n",
       " -0.04956040903925896,\n",
       " 0.013426685705780983,\n",
       " 0.04726368933916092,\n",
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       " -0.002763529308140278,\n",
       " 0.041928499937057495,\n",
       " -0.05356898531317711,\n",
       " 0.0539068877696991,\n",
       " -0.018068518489599228,\n",
       " 0.025555135682225227,\n",
       " -0.006111381109803915,\n",
       " -0.021271517500281334,\n",
       " -0.07312703132629395,\n",
       " 0.01476153265684843,\n",
       " 0.012981124222278595,\n",
       " 0.003919216804206371,\n",
       " 0.0145395677536726,\n",
       " 0.00764697277918458,\n",
       " -0.04976822808384895,\n",
       " 0.05506889894604683,\n",
       " -0.10115853697061539,\n",
       " 0.08098918944597244,\n",
       " 0.06652805209159851,\n",
       " -0.05758703872561455,\n",
       " -0.004396950826048851,\n",
       " 0.028381312265992165,\n",
       " 0.0681462362408638,\n",
       " 0.0003248592547606677,\n",
       " -0.013774129562079906,\n",
       " -0.02230236865580082,\n",
       " -0.02134030871093273,\n",
       " 0.044915515929460526,\n",
       " ...]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check node embeddings\n",
    "emb_dict = biobridge_data.get_node_embeddings()\n",
    "emb_dict[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "85466"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(emb_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2560"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check embedding dimension\n",
    "len(emb_dict[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>node_index</th>\n",
       "      <th>node_name</th>\n",
       "      <th>node_source</th>\n",
       "      <th>node_id</th>\n",
       "      <th>node_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>PHYHIP</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>9796</td>\n",
       "      <td>gene/protein</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   node_index node_name node_source node_id     node_type\n",
       "0           0    PHYHIP        NCBI    9796  gene/protein"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Cross-check the node embeddings with the node types\n",
    "primekg_nodes[primekg_nodes.node_index == 0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check Triplet Splits of BioBridge-PrimeKG"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lastly, BioBridge-PrimeKG splits contain train and test dataframes of triplets and nodes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>head_index</th>\n",
       "      <th>head_name</th>\n",
       "      <th>head_source</th>\n",
       "      <th>head_id</th>\n",
       "      <th>head_type</th>\n",
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       "      <th>relation</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>PHYHIP</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>9796</td>\n",
       "      <td>1</td>\n",
       "      <td>8889</td>\n",
       "      <td>KIF15</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>56992</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>GPANK1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>7918</td>\n",
       "      <td>1</td>\n",
       "      <td>2798</td>\n",
       "      <td>PNMA1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>9240</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>ZRSR2</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>8233</td>\n",
       "      <td>1</td>\n",
       "      <td>5646</td>\n",
       "      <td>TTC33</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>23548</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>NRF1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>4899</td>\n",
       "      <td>1</td>\n",
       "      <td>11592</td>\n",
       "      <td>MAN1B1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>11253</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>PI4KA</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>5297</td>\n",
       "      <td>1</td>\n",
       "      <td>2122</td>\n",
       "      <td>RGS20</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>8601</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   head_index head_name head_source head_id  head_type  tail_index tail_name  \\\n",
       "0           0    PHYHIP        NCBI    9796          1        8889     KIF15   \n",
       "1           1    GPANK1        NCBI    7918          1        2798     PNMA1   \n",
       "2           2     ZRSR2        NCBI    8233          1        5646     TTC33   \n",
       "3           3      NRF1        NCBI    4899          1       11592    MAN1B1   \n",
       "4           4     PI4KA        NCBI    5297          1        2122     RGS20   \n",
       "\n",
       "  tail_source tail_id  tail_type  display_relation         relation  \n",
       "0        NCBI   56992          1                 3  protein_protein  \n",
       "1        NCBI    9240          1                 3  protein_protein  \n",
       "2        NCBI   23548          1                 3  protein_protein  \n",
       "3        NCBI   11253          1                 3  protein_protein  \n",
       "4        NCBI    8601          1                 3  protein_protein  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get all triplets of BioBridge PrimeKG\n",
    "triplets = biobridge_data.get_primekg_triplets()\n",
    "triplets.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>0</th>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <th>2</th>\n",
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       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>NRF1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>4899</td>\n",
       "      <td>1</td>\n",
       "      <td>11592</td>\n",
       "      <td>MAN1B1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>11253</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>PI4KA</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>5297</td>\n",
       "      <td>1</td>\n",
       "      <td>2122</td>\n",
       "      <td>RGS20</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>8601</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3904605</th>\n",
       "      <td>52855</td>\n",
       "      <td>B cell receptor transport into membrane raft</td>\n",
       "      <td>GO</td>\n",
       "      <td>32597</td>\n",
       "      <td>0</td>\n",
       "      <td>34572</td>\n",
       "      <td>CD24</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>100133941</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>bioprocess_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3904606</th>\n",
       "      <td>113352</td>\n",
       "      <td>chemokine receptor transport out of membrane raft</td>\n",
       "      <td>GO</td>\n",
       "      <td>32600</td>\n",
       "      <td>0</td>\n",
       "      <td>34572</td>\n",
       "      <td>CD24</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>100133941</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>bioprocess_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3904607</th>\n",
       "      <td>42264</td>\n",
       "      <td>negative regulation of cytoskeleton organization</td>\n",
       "      <td>GO</td>\n",
       "      <td>51494</td>\n",
       "      <td>0</td>\n",
       "      <td>57675</td>\n",
       "      <td>IQCJ-SCHIP1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>100505385</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>bioprocess_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3904608</th>\n",
       "      <td>109904</td>\n",
       "      <td>mesendoderm migration</td>\n",
       "      <td>GO</td>\n",
       "      <td>90133</td>\n",
       "      <td>0</td>\n",
       "      <td>58770</td>\n",
       "      <td>APELA</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>100506013</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>bioprocess_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3904609</th>\n",
       "      <td>44810</td>\n",
       "      <td>regulation of endoplasmic reticulum unfolded p...</td>\n",
       "      <td>GO</td>\n",
       "      <td>1900101</td>\n",
       "      <td>0</td>\n",
       "      <td>57692</td>\n",
       "      <td>PIGBOS1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>101928527</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>bioprocess_protein</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3904610 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         head_index                                          head_name  \\\n",
       "0                 0                                             PHYHIP   \n",
       "1                 1                                             GPANK1   \n",
       "2                 2                                              ZRSR2   \n",
       "3                 3                                               NRF1   \n",
       "4                 4                                              PI4KA   \n",
       "...             ...                                                ...   \n",
       "3904605       52855       B cell receptor transport into membrane raft   \n",
       "3904606      113352  chemokine receptor transport out of membrane raft   \n",
       "3904607       42264   negative regulation of cytoskeleton organization   \n",
       "3904608      109904                              mesendoderm migration   \n",
       "3904609       44810  regulation of endoplasmic reticulum unfolded p...   \n",
       "\n",
       "        head_source  head_id  head_type  tail_index    tail_name tail_source  \\\n",
       "0              NCBI     9796          1        8889        KIF15        NCBI   \n",
       "1              NCBI     7918          1        2798        PNMA1        NCBI   \n",
       "2              NCBI     8233          1        5646        TTC33        NCBI   \n",
       "3              NCBI     4899          1       11592       MAN1B1        NCBI   \n",
       "4              NCBI     5297          1        2122        RGS20        NCBI   \n",
       "...             ...      ...        ...         ...          ...         ...   \n",
       "3904605          GO    32597          0       34572         CD24        NCBI   \n",
       "3904606          GO    32600          0       34572         CD24        NCBI   \n",
       "3904607          GO    51494          0       57675  IQCJ-SCHIP1        NCBI   \n",
       "3904608          GO    90133          0       58770        APELA        NCBI   \n",
       "3904609          GO  1900101          0       57692      PIGBOS1        NCBI   \n",
       "\n",
       "           tail_id  tail_type  display_relation            relation  \n",
       "0            56992          1                 3     protein_protein  \n",
       "1             9240          1                 3     protein_protein  \n",
       "2            23548          1                 3     protein_protein  \n",
       "3            11253          1                 3     protein_protein  \n",
       "4             8601          1                 3     protein_protein  \n",
       "...            ...        ...               ...                 ...  \n",
       "3904605  100133941          1                 2  bioprocess_protein  \n",
       "3904606  100133941          1                 2  bioprocess_protein  \n",
       "3904607  100505385          1                 2  bioprocess_protein  \n",
       "3904608  100506013          1                 2  bioprocess_protein  \n",
       "3904609  101928527          1                 2  bioprocess_protein  \n",
       "\n",
       "[3904610 rows x 12 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "triplets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we can check the number of each split as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Check the number of samples in each split of the biobridge primekg dataframes\n",
    "biobridge_splits = biobridge_data.get_train_test_split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['train', 'node_train', 'test', 'node_test']"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(biobridge_splits.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "      <th>head_name</th>\n",
       "      <th>head_source</th>\n",
       "      <th>head_id</th>\n",
       "      <th>head_type</th>\n",
       "      <th>tail_index</th>\n",
       "      <th>tail_name</th>\n",
       "      <th>tail_source</th>\n",
       "      <th>tail_id</th>\n",
       "      <th>tail_type</th>\n",
       "      <th>display_relation</th>\n",
       "      <th>relation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>PHYHIP</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>9796</td>\n",
       "      <td>1</td>\n",
       "      <td>8889</td>\n",
       "      <td>KIF15</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>56992</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>GPANK1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>7918</td>\n",
       "      <td>1</td>\n",
       "      <td>2798</td>\n",
       "      <td>PNMA1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>9240</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>ZRSR2</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>8233</td>\n",
       "      <td>1</td>\n",
       "      <td>5646</td>\n",
       "      <td>TTC33</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>23548</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>NRF1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>4899</td>\n",
       "      <td>1</td>\n",
       "      <td>11592</td>\n",
       "      <td>MAN1B1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>11253</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>PI4KA</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>5297</td>\n",
       "      <td>1</td>\n",
       "      <td>2122</td>\n",
       "      <td>RGS20</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>8601</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3768281</th>\n",
       "      <td>124473</td>\n",
       "      <td>longitudinal sarcoplasmic reticulum</td>\n",
       "      <td>GO</td>\n",
       "      <td>14801</td>\n",
       "      <td>7</td>\n",
       "      <td>58744</td>\n",
       "      <td>DHRS7C</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>201140</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>cellcomp_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3768282</th>\n",
       "      <td>55747</td>\n",
       "      <td>myofilament</td>\n",
       "      <td>GO</td>\n",
       "      <td>36379</td>\n",
       "      <td>7</td>\n",
       "      <td>57367</td>\n",
       "      <td>MYBPHL</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>343263</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>cellcomp_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3768285</th>\n",
       "      <td>126945</td>\n",
       "      <td>lateral wall of outer hair cell</td>\n",
       "      <td>GO</td>\n",
       "      <td>120249</td>\n",
       "      <td>7</td>\n",
       "      <td>22033</td>\n",
       "      <td>SLC26A5</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>375611</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>cellcomp_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3768286</th>\n",
       "      <td>125456</td>\n",
       "      <td>Swi5-Swi2 complex</td>\n",
       "      <td>GO</td>\n",
       "      <td>34974</td>\n",
       "      <td>7</td>\n",
       "      <td>57415</td>\n",
       "      <td>SWI5</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>375757</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>cellcomp_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3768287</th>\n",
       "      <td>55667</td>\n",
       "      <td>SUMO ligase complex</td>\n",
       "      <td>GO</td>\n",
       "      <td>106068</td>\n",
       "      <td>7</td>\n",
       "      <td>35398</td>\n",
       "      <td>SUMO4</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>387082</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>cellcomp_protein</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3510930 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         head_index                            head_name head_source head_id  \\\n",
       "0                 0                               PHYHIP        NCBI    9796   \n",
       "1                 1                               GPANK1        NCBI    7918   \n",
       "2                 2                                ZRSR2        NCBI    8233   \n",
       "3                 3                                 NRF1        NCBI    4899   \n",
       "4                 4                                PI4KA        NCBI    5297   \n",
       "...             ...                                  ...         ...     ...   \n",
       "3768281      124473  longitudinal sarcoplasmic reticulum          GO   14801   \n",
       "3768282       55747                          myofilament          GO   36379   \n",
       "3768285      126945      lateral wall of outer hair cell          GO  120249   \n",
       "3768286      125456                    Swi5-Swi2 complex          GO   34974   \n",
       "3768287       55667                  SUMO ligase complex          GO  106068   \n",
       "\n",
       "         head_type  tail_index tail_name tail_source tail_id  tail_type  \\\n",
       "0                1        8889     KIF15        NCBI   56992          1   \n",
       "1                1        2798     PNMA1        NCBI    9240          1   \n",
       "2                1        5646     TTC33        NCBI   23548          1   \n",
       "3                1       11592    MAN1B1        NCBI   11253          1   \n",
       "4                1        2122     RGS20        NCBI    8601          1   \n",
       "...            ...         ...       ...         ...     ...        ...   \n",
       "3768281          7       58744    DHRS7C        NCBI  201140          1   \n",
       "3768282          7       57367    MYBPHL        NCBI  343263          1   \n",
       "3768285          7       22033   SLC26A5        NCBI  375611          1   \n",
       "3768286          7       57415      SWI5        NCBI  375757          1   \n",
       "3768287          7       35398     SUMO4        NCBI  387082          1   \n",
       "\n",
       "         display_relation          relation  \n",
       "0                       3   protein_protein  \n",
       "1                       3   protein_protein  \n",
       "2                       3   protein_protein  \n",
       "3                       3   protein_protein  \n",
       "4                       3   protein_protein  \n",
       "...                   ...               ...  \n",
       "3768281                 2  cellcomp_protein  \n",
       "3768282                 2  cellcomp_protein  \n",
       "3768285                 2  cellcomp_protein  \n",
       "3768286                 2  cellcomp_protein  \n",
       "3768287                 2  cellcomp_protein  \n",
       "\n",
       "[3510930 rows x 12 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check dataframe of training triples\n",
    "biobridge_splits[\"train\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>node_type</th>\n",
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       "      <th>...</th>\n",
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       "      <th>76482</th>\n",
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       "      <th>76483</th>\n",
       "      <td>127433</td>\n",
       "      <td>7</td>\n",
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       "      <th>76485</th>\n",
       "      <td>127316</td>\n",
       "      <td>7</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>76486 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       node_index  node_type\n",
       "0               0          1\n",
       "1               1          1\n",
       "2               2          1\n",
       "3               3          1\n",
       "4               4          1\n",
       "...           ...        ...\n",
       "76481      127431          7\n",
       "76482      127432          7\n",
       "76483      127433          7\n",
       "76484      127239          7\n",
       "76485      127316          7\n",
       "\n",
       "[76486 rows x 2 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check dataframe of training nodes\n",
    "biobridge_splits[\"node_train\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>head_index</th>\n",
       "      <th>head_name</th>\n",
       "      <th>head_source</th>\n",
       "      <th>head_id</th>\n",
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       "      <th>tail_index</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>MT1A</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>4489</td>\n",
       "      <td>1</td>\n",
       "      <td>1785</td>\n",
       "      <td>TP53</td>\n",
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       "      <td>924</td>\n",
       "      <td>1</td>\n",
       "      <td>7681</td>\n",
       "      <td>SFXN5</td>\n",
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       "      <td>94097</td>\n",
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       "      <td>3</td>\n",
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       "      <th>16</th>\n",
       "      <td>16</td>\n",
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       "      <td>6633</td>\n",
       "      <td>1</td>\n",
       "      <td>3235</td>\n",
       "      <td>PRPF4</td>\n",
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       "      <td>9128</td>\n",
       "      <td>1</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>VAV3</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>10451</td>\n",
       "      <td>1</td>\n",
       "      <td>3005</td>\n",
       "      <td>ZRANB1</td>\n",
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       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</td>\n",
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       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>16</td>\n",
       "      <td>SNRPD2</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>6633</td>\n",
       "      <td>1</td>\n",
       "      <td>216</td>\n",
       "      <td>NCSTN</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>23385</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>protein_protein</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3768273</th>\n",
       "      <td>125342</td>\n",
       "      <td>myosin V complex</td>\n",
       "      <td>GO</td>\n",
       "      <td>31475</td>\n",
       "      <td>7</td>\n",
       "      <td>9639</td>\n",
       "      <td>DYNLL2</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>140735</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>cellcomp_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3768277</th>\n",
       "      <td>55608</td>\n",
       "      <td>extracellular membrane-bounded organelle</td>\n",
       "      <td>GO</td>\n",
       "      <td>65010</td>\n",
       "      <td>7</td>\n",
       "      <td>57129</td>\n",
       "      <td>PHOSPHO1</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>162466</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>cellcomp_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3768283</th>\n",
       "      <td>124243</td>\n",
       "      <td>axonemal outer doublet</td>\n",
       "      <td>GO</td>\n",
       "      <td>97545</td>\n",
       "      <td>7</td>\n",
       "      <td>59351</td>\n",
       "      <td>CFAP100</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>348807</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>cellcomp_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3768284</th>\n",
       "      <td>124243</td>\n",
       "      <td>axonemal outer doublet</td>\n",
       "      <td>GO</td>\n",
       "      <td>97545</td>\n",
       "      <td>7</td>\n",
       "      <td>59352</td>\n",
       "      <td>CFAP73</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>387885</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>cellcomp_protein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3768288</th>\n",
       "      <td>126258</td>\n",
       "      <td>uropod membrane</td>\n",
       "      <td>GO</td>\n",
       "      <td>31259</td>\n",
       "      <td>7</td>\n",
       "      <td>57434</td>\n",
       "      <td>SCIMP</td>\n",
       "      <td>NCBI</td>\n",
       "      <td>388325</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>cellcomp_protein</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>393680 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         head_index                                 head_name head_source  \\\n",
       "8                 8                                      MT1A        NCBI   \n",
       "12               12                                       CD7        NCBI   \n",
       "16               16                                    SNRPD2        NCBI   \n",
       "18               19                                      VAV3        NCBI   \n",
       "29               16                                    SNRPD2        NCBI   \n",
       "...             ...                                       ...         ...   \n",
       "3768273      125342                          myosin V complex          GO   \n",
       "3768277       55608  extracellular membrane-bounded organelle          GO   \n",
       "3768283      124243                    axonemal outer doublet          GO   \n",
       "3768284      124243                    axonemal outer doublet          GO   \n",
       "3768288      126258                           uropod membrane          GO   \n",
       "\n",
       "        head_id  head_type  tail_index tail_name tail_source tail_id  \\\n",
       "8          4489          1        1785      TP53        NCBI    7157   \n",
       "12          924          1        7681     SFXN5        NCBI   94097   \n",
       "16         6633          1        3235     PRPF4        NCBI    9128   \n",
       "18        10451          1        3005    ZRANB1        NCBI   54764   \n",
       "29         6633          1         216     NCSTN        NCBI   23385   \n",
       "...         ...        ...         ...       ...         ...     ...   \n",
       "3768273   31475          7        9639    DYNLL2        NCBI  140735   \n",
       "3768277   65010          7       57129  PHOSPHO1        NCBI  162466   \n",
       "3768283   97545          7       59351   CFAP100        NCBI  348807   \n",
       "3768284   97545          7       59352    CFAP73        NCBI  387885   \n",
       "3768288   31259          7       57434     SCIMP        NCBI  388325   \n",
       "\n",
       "         tail_type  display_relation          relation  \n",
       "8                1                 3   protein_protein  \n",
       "12               1                 3   protein_protein  \n",
       "16               1                 3   protein_protein  \n",
       "18               1                 3   protein_protein  \n",
       "29               1                 3   protein_protein  \n",
       "...            ...               ...               ...  \n",
       "3768273          1                 2  cellcomp_protein  \n",
       "3768277          1                 2  cellcomp_protein  \n",
       "3768283          1                 2  cellcomp_protein  \n",
       "3768284          1                 2  cellcomp_protein  \n",
       "3768288          1                 2  cellcomp_protein  \n",
       "\n",
       "[393680 rows x 12 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check dataframe of testing triples\n",
    "biobridge_splits[\"test\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>node_index</th>\n",
       "      <th>node_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8490</th>\n",
       "      <td>127404</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8491</th>\n",
       "      <td>127415</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8492</th>\n",
       "      <td>127421</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8493</th>\n",
       "      <td>127425</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8494</th>\n",
       "      <td>127434</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8495 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      node_index  node_type\n",
       "0              8          1\n",
       "1             12          1\n",
       "2             16          1\n",
       "3             19          1\n",
       "4             34          1\n",
       "...          ...        ...\n",
       "8490      127404          7\n",
       "8491      127415          7\n",
       "8492      127421          7\n",
       "8493      127425          7\n",
       "8494      127434          7\n",
       "\n",
       "[8495 rows x 2 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check dataframe of testing nodes\n",
    "biobridge_splits[\"node_test\"]"
   ]
  }
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