notebooks/queries/FulltextQuery.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Examples of Full-text queries in the COVID-19-Net Knowledge Graph\n",
    "[Work in progress]\n",
    "\n",
    "This notebook demonstrates how to run full-text [Lucene queries](https://lucene.apache.org/core/5_5_0/queryparser/org/apache/lucene/queryparser/classic/package-summary.html#Overview) in the Knowledge Graph. \n",
    "\n",
    "COVID-19-Net KG supports text searches for the following types of entities\n",
    "* bioentities: full-text query for biological entities (proteins, genes, domains, etc.)\n",
    "* locations: full-text query for locations (cities, counties, states, countries, etc.)\n",
    "* sequences: full-text search for protein sequences\n",
    "* geoids: keyword (exact) query for geographic identifiers (zip codes, fips codes, iso codes, etc.)\n",
    "\n",
    "Full-text queries have the following format\n",
    "\n",
    "```CALL db.index.fulltext.queryNodes('<type of entity>', '<text query>') YIELD node, score```\n",
    "\n",
    "The queries return the matching nodes, and a score for each match (higher scores indicate better matches).\n",
    "\n",
    "[Query Syntax](https://lucene.apache.org/core/5_5_0/queryparser/org/apache/lucene/queryparser/classic/package-summary.html#Overview)\n",
    "\n",
    "[Learn more about full-text searches](https://graphaware.com/neo4j/2019/01/11/neo4j-full-text-search-deep-dive.html).\n",
    "\n",
    "Author: Peter W. Rose (pwrose@ucsd.edu)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "import pandas as pd\n",
    "from py2neo import Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.display.max_rows = None  # display all rows\n",
    "pd.options.display.max_columns = None  # display all columsns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Connect to COVID-19-Net Knowledge Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "graph = Graph(\"bolt://132.249.238.185:7687\", user=\"reader\", password=\"demo\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Full-text Query for a term (word)\n",
    "Results are ordered by match score ([TermsQuery](https://lucene.apache.org/core/5_5_5/queries/org/apache/lucene/queries/TermsQuery.html)).\n",
    "Note, full-text queries are case insensitive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 406\n"
     ]
    },
    {
     "data": {
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.255547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.255547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.255547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.255547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>spike protein</td>\n",
       "      <td>[ProteinName]</td>\n",
       "      <td>5.255547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>[ProteinName]</td>\n",
       "      <td>5.255547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>[ProteinName]</td>\n",
       "      <td>5.255547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.255547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.255547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>[ProteinName]</td>\n",
       "      <td>5.255547</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 name   labels(node)     score\n",
       "0  Spike glycoprotein      [Protein]  5.255547\n",
       "1  Spike glycoprotein      [Protein]  5.255547\n",
       "2  Spike glycoprotein      [Protein]  5.255547\n",
       "3  Spike glycoprotein      [Protein]  5.255547\n",
       "4       spike protein  [ProteinName]  5.255547\n",
       "5  Spike glycoprotein  [ProteinName]  5.255547\n",
       "6  Spike glycoprotein  [ProteinName]  5.255547\n",
       "7  Spike glycoprotein      [Protein]  5.255547\n",
       "8  Spike glycoprotein      [Protein]  5.255547\n",
       "9  Spike glycoprotein  [ProteinName]  5.255547"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This query searches for the term \"Spike\" in the bioentities.\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('bioentities', 'Spike') YIELD node, score\n",
    "RETURN node.name AS name, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Search for an exact Phrase \n",
    "For exact matches, enclose the phrase in **double** quotes ([PhraseQuery](https://lucene.apache.org/core/5_5_0/core/org/apache/lucene/search/PhraseQuery.html))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 14\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>fullLength</th>\n",
       "      <th>accession</th>\n",
       "      <th>proId</th>\n",
       "      <th>taxonomy</th>\n",
       "      <th>sequence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>1</td>\n",
       "      <td>1173</td>\n",
       "      <td>True</td>\n",
       "      <td>uniprot:P15423</td>\n",
       "      <td>None</td>\n",
       "      <td>taxonomy:11137</td>\n",
       "      <td>MFVLLVAYALLHIAGCQTTNGLNTSYSVCNGCVGYSENVFAVESGG...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>16</td>\n",
       "      <td>1173</td>\n",
       "      <td>False</td>\n",
       "      <td>uniprot:P15423</td>\n",
       "      <td>uniprot.chain:PRO_0000037203</td>\n",
       "      <td>taxonomy:11137</td>\n",
       "      <td>CQTTNGLNTSYSVCNGCVGYSENVFAVESGGYIPSDFAFNNWFLLT...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>1</td>\n",
       "      <td>1353</td>\n",
       "      <td>True</td>\n",
       "      <td>uniprot:K9N5Q8</td>\n",
       "      <td>None</td>\n",
       "      <td>taxonomy:1263720</td>\n",
       "      <td>MIHSVFLLMFLLTPTESYVDVGPDSVKSACIEVDIQQTFFDKTWPR...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>18</td>\n",
       "      <td>1353</td>\n",
       "      <td>False</td>\n",
       "      <td>uniprot:K9N5Q8</td>\n",
       "      <td>uniprot.chain:PRO_0000422465</td>\n",
       "      <td>taxonomy:1263720</td>\n",
       "      <td>YVDVGPDSVKSACIEVDIQQTFFDKTWPRPIDVSKADGIIYPQGRT...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Spike glycoprotein</td>\n",
       "      <td>1</td>\n",
       "      <td>1273</td>\n",
       "      <td>True</td>\n",
       "      <td>uniprot:P0DTC2</td>\n",
       "      <td>None</td>\n",
       "      <td>taxonomy:2697049</td>\n",
       "      <td>MFVFLVLLPLVSSQCVNLTTRTQLPPAYTNSFTRGVYYPDKVFRSS...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 name  start   end fullLength       accession  \\\n",
       "0  Spike glycoprotein      1  1173       True  uniprot:P15423   \n",
       "1  Spike glycoprotein     16  1173      False  uniprot:P15423   \n",
       "2  Spike glycoprotein      1  1353       True  uniprot:K9N5Q8   \n",
       "3  Spike glycoprotein     18  1353      False  uniprot:K9N5Q8   \n",
       "4  Spike glycoprotein      1  1273       True  uniprot:P0DTC2   \n",
       "\n",
       "                          proId          taxonomy  \\\n",
       "0                          None    taxonomy:11137   \n",
       "1  uniprot.chain:PRO_0000037203    taxonomy:11137   \n",
       "2                          None  taxonomy:1263720   \n",
       "3  uniprot.chain:PRO_0000422465  taxonomy:1263720   \n",
       "4                          None  taxonomy:2697049   \n",
       "\n",
       "                                            sequence  \n",
       "0  MFVLLVAYALLHIAGCQTTNGLNTSYSVCNGCVGYSENVFAVESGG...  \n",
       "1  CQTTNGLNTSYSVCNGCVGYSENVFAVESGGYIPSDFAFNNWFLLT...  \n",
       "2  MIHSVFLLMFLLTPTESYVDVGPDSVKSACIEVDIQQTFFDKTWPR...  \n",
       "3  YVDVGPDSVKSACIEVDIQQTFFDKTWPRPIDVSKADGIIYPQGRT...  \n",
       "4  MFVFLVLLPLVSSQCVNLTTRTQLPPAYTNSFTRGVYYPDKVFRSS...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This query searches for the exact phrase \"Spike glycoprotein\" in the bioentities.\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('bioentities', '\"Spike glycoprotein\"') YIELD node\n",
    "WHERE 'Protein' IN labels(node)\n",
    "RETURN node.name AS name, node.start as start, node.end AS end, node.fullLength AS fullLength, node.accession AS accession, node.proId as proId, \n",
    "       node.taxonomyId AS taxonomy, node.sequence AS sequence\n",
    "ORDER BY taxonomy, start\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Node Property Query\n",
    "Queries can be restricted to a specific node property name: `<node property>: <term>`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 1\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>name</th>\n",
       "      <th>node.scientificName</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>human</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>[Organism]</td>\n",
       "      <td>2.801928</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name node.scientificName labels(node)     score\n",
       "0  human        Homo sapiens   [Organism]  2.801928"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This query matches nodes with the node property 'scientificName'\n",
    "\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('bioentities', 'scientificName: \"Homo sapiens\"') YIELD node, score\n",
    "RETURN node.name AS name, node.scientificName, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head(15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fuzzy Query\n",
    "A fuzzy query finds approximate matches by adding a tilde `~` at the end of the query term\n",
    "([FuzzyQuery](https://lucene.apache.org/core/5_5_0/core/org/apache/lucene/search/FuzzyQuery.html))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 4172\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>description</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Proteasome</td>\n",
       "      <td>Proteasome subunit</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>7.068081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Prostase</td>\n",
       "      <td>None</td>\n",
       "      <td>[ProteinName]</td>\n",
       "      <td>6.422506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>pdb:4CR2</td>\n",
       "      <td>PROTEASOME COMPONENT PRE3, PROTEASOME COMPONEN...</td>\n",
       "      <td>[Structure]</td>\n",
       "      <td>5.389273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>pdb:4CR3</td>\n",
       "      <td>PROTEASOME COMPONENT PRE3, PROTEASOME COMPONEN...</td>\n",
       "      <td>[Structure]</td>\n",
       "      <td>5.389273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pdb:4CR4</td>\n",
       "      <td>PROTEASOME COMPONENT PRE3, PROTEASOME COMPONEN...</td>\n",
       "      <td>[Structure]</td>\n",
       "      <td>5.389273</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name                                        description  \\\n",
       "0  Proteasome                                 Proteasome subunit   \n",
       "1    Prostase                                               None   \n",
       "2    pdb:4CR2  PROTEASOME COMPONENT PRE3, PROTEASOME COMPONEN...   \n",
       "3    pdb:4CR3  PROTEASOME COMPONENT PRE3, PROTEASOME COMPONEN...   \n",
       "4    pdb:4CR4  PROTEASOME COMPONENT PRE3, PROTEASOME COMPONEN...   \n",
       "\n",
       "    labels(node)     score  \n",
       "0       [Domain]  7.068081  \n",
       "1  [ProteinName]  6.422506  \n",
       "2    [Structure]  5.389273  \n",
       "3    [Structure]  5.389273  \n",
       "4    [Structure]  5.389273  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This query does a fuzzy search for the term \"protease\" in the bioentities. \n",
    "# It matches terms such as \"proteinase\" or \"proteasome\".\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('bioentities', 'protease~') YIELD node, score\n",
    "RETURN node.name AS name, node.description AS description, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fuzzy query with Similarity Threshold\n",
    "The similary threshold [0.0 .. 1.0] can be specified in a fuzzy query (default 0.5)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 393\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>placeName</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>81120</td>\n",
       "      <td>Antonito</td>\n",
       "      <td>[Location, PostalCode]</td>\n",
       "      <td>4.358802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Saint-Antonin</td>\n",
       "      <td>None</td>\n",
       "      <td>[Location, City]</td>\n",
       "      <td>3.965481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maria Antonia</td>\n",
       "      <td>None</td>\n",
       "      <td>[Location, City]</td>\n",
       "      <td>3.965481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sant Antoni</td>\n",
       "      <td>None</td>\n",
       "      <td>[Location, City]</td>\n",
       "      <td>3.590200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sankt Antoni</td>\n",
       "      <td>None</td>\n",
       "      <td>[Location, City]</td>\n",
       "      <td>3.590200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            name placeName            labels(node)     score\n",
       "0          81120  Antonito  [Location, PostalCode]  4.358802\n",
       "1  Saint-Antonin      None        [Location, City]  3.965481\n",
       "2  Maria Antonia      None        [Location, City]  3.965481\n",
       "3    Sant Antoni      None        [Location, City]  3.590200\n",
       "4   Sankt Antoni      None        [Location, City]  3.590200"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This query searches for the location \"antonio\" with a similarity threshold of 0.8.\n",
    "\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('locations', 'antonio~0.8') YIELD node, score\n",
    "RETURN node.name AS name, node.placeName as placeName, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fuzzy Query with Edit Distance\n",
    "Lucene supports fuzzy searches based on [Damerau-Levenshtein Distance](https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance). To do a fuzzy search use the tilde, `~`, symbol at the end of a Single word Term. The maximum number of edits (substitutions, deletions, and insertions) can be specified after the tile, e.g. `~3` to search for matches with up to 3 edits."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 2\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>node.sequence</th>\n",
       "      <th>node.accession</th>\n",
       "      <th>node.taxonomyId</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Non-structural protein 11</td>\n",
       "      <td>SADAQSFLNGFAV</td>\n",
       "      <td>uniprot:P0DTC1</td>\n",
       "      <td>taxonomy:2697049</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.965485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Non-structural protein 11</td>\n",
       "      <td>SADASTFLNGFAV</td>\n",
       "      <td>uniprot:P0C6U8</td>\n",
       "      <td>taxonomy:694009</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.047718</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        name  node.sequence  node.accession   node.taxonomyId  \\\n",
       "0  Non-structural protein 11  SADAQSFLNGFAV  uniprot:P0DTC1  taxonomy:2697049   \n",
       "1  Non-structural protein 11  SADASTFLNGFAV  uniprot:P0C6U8   taxonomy:694009   \n",
       "\n",
       "  labels(node)     score  \n",
       "0    [Protein]  5.965485  \n",
       "1    [Protein]  5.047718  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find matches that contain sequences similar to SADAQSFLNGFAV with up to 3 edits (e.g. substitutions)\n",
    "# This query returns two results:\n",
    "#    exact match for nsp11 protein (SARS-CoV-2, taxonomyId:2697049) \n",
    "#    approximate match for nsp11 protein (SARS-CoV, taxonomyId:694009) with 2 substitutions QS -> ST\n",
    "\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('sequences', 'SADAQSFLNGFAV~3') YIELD node, score\n",
    "RETURN node.name AS name, node.sequence, node.accession, node.taxonomyId, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Wildcard Query\n",
    "Wildcards are used to search for alternate spellings and variations on a root word. A `*` matches multiple characters and a `?` matches a single character\n",
    "([WildcardQuery](https://lucene.apache.org/core/5_5_5/core/org/apache/lucene/search/WildcardQuery.html))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 7814\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>name</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Polysacc_deac_1</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Polyketide_cyc2</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>polyprenyl_synt</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Polyoma_coat</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Polysacc_synt_2</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              name labels(node)  score\n",
       "0  Polysacc_deac_1     [Domain]    2.0\n",
       "1  Polyketide_cyc2     [Domain]    2.0\n",
       "2  polyprenyl_synt     [Domain]    2.0\n",
       "3     Polyoma_coat     [Domain]    2.0\n",
       "4  Polysacc_synt_2     [Domain]    2.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This query matches terms that start with \"poly\". \"*\" matches zero or more characters.\n",
    "\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('bioentities', 'poly*') YIELD node, score\n",
    "RETURN node.name AS name, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 14908\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>name</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Rap1-DNA-bind</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>PTS_2-RNA</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MerR-DNA-bind</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Arm-DNA-bind_3</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Arm-DNA-bind_1</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Cauli_DNA-bind</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Drc1-Sld2</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>SLD3</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Methyltrn_RNA_4</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>DMP12</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              name labels(node)  score\n",
       "0    Rap1-DNA-bind     [Domain]    2.0\n",
       "1        PTS_2-RNA     [Domain]    2.0\n",
       "2    MerR-DNA-bind     [Domain]    2.0\n",
       "3   Arm-DNA-bind_3     [Domain]    2.0\n",
       "4   Arm-DNA-bind_1     [Domain]    2.0\n",
       "5   Cauli_DNA-bind     [Domain]    1.0\n",
       "6        Drc1-Sld2     [Domain]    1.0\n",
       "7             SLD3     [Domain]    1.0\n",
       "8  Methyltrn_RNA_4     [Domain]    1.0\n",
       "9            DMP12     [Domain]    1.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This query matches the terms RNA and DNA.\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('bioentities', '?NA') YIELD node, score\n",
    "RETURN node.name AS name, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Boolean expressions in queries\n",
    "Boolean operators `OR` and `AND` can be specified in searches."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### OR operator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 14877\n"
     ]
    },
    {
     "data": {
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       "<style scoped>\n",
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       "    }\n",
       "\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>name</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DNA-directed DNA/RNA polymerase mu</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.980085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DNA-directed DNA/RNA polymerase mu</td>\n",
       "      <td>[ProteinName]</td>\n",
       "      <td>5.980085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>PTS_2-RNA</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>5.875489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rap1-DNA-bind</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>5.485790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MerR-DNA-bind</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>5.485790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Arm-DNA-bind_3</td>\n",
       "      <td>[Domain]</td>\n",
       "      <td>5.414452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>DNA-directed RNA polymerase, mitochondrial</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.257301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>DNA/RNA-binding protein KIN17</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.257301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DNA-directed RNA polymerase, mitochondrial</td>\n",
       "      <td>[ProteinName]</td>\n",
       "      <td>5.257301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>DNA-directed RNA polymerase, mitochondrial</td>\n",
       "      <td>[ProteinName]</td>\n",
       "      <td>5.257301</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         name   labels(node)     score\n",
       "0          DNA-directed DNA/RNA polymerase mu      [Protein]  5.980085\n",
       "1          DNA-directed DNA/RNA polymerase mu  [ProteinName]  5.980085\n",
       "2                                   PTS_2-RNA       [Domain]  5.875489\n",
       "3                               Rap1-DNA-bind       [Domain]  5.485790\n",
       "4                               MerR-DNA-bind       [Domain]  5.485790\n",
       "5                              Arm-DNA-bind_3       [Domain]  5.414452\n",
       "6  DNA-directed RNA polymerase, mitochondrial      [Protein]  5.257301\n",
       "7               DNA/RNA-binding protein KIN17      [Protein]  5.257301\n",
       "8  DNA-directed RNA polymerase, mitochondrial  [ProteinName]  5.257301\n",
       "9  DNA-directed RNA polymerase, mitochondrial  [ProteinName]  5.257301"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find matches for the terms RNA or DNA.\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('bioentities', 'DNA OR RNA') YIELD node, score\n",
    "RETURN node.name AS name, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### AND operator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 1278\n"
     ]
    },
    {
     "data": {
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       "<style scoped>\n",
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       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DNA-directed DNA/RNA polymerase mu</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.980085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DNA-directed DNA/RNA polymerase mu</td>\n",
       "      <td>[ProteinName]</td>\n",
       "      <td>5.980085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DNA-directed RNA polymerase, mitochondrial</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.257301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DNA-directed RNA polymerase, mitochondrial</td>\n",
       "      <td>[ProteinName]</td>\n",
       "      <td>5.257301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DNA-directed RNA polymerase, mitochondrial</td>\n",
       "      <td>[ProteinName]</td>\n",
       "      <td>5.257301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>DNA/RNA-binding protein KIN17</td>\n",
       "      <td>[ProteinName]</td>\n",
       "      <td>5.257301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>DNA/RNA-binding protein KIN17</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.257301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>DNA-directed RNA polymerase, mitochondrial</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.257301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>pdb:4QIW</td>\n",
       "      <td>[Structure]</td>\n",
       "      <td>4.875343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>pdb:6KF3</td>\n",
       "      <td>[Structure]</td>\n",
       "      <td>4.851152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         name   labels(node)     score\n",
       "0          DNA-directed DNA/RNA polymerase mu      [Protein]  5.980085\n",
       "1          DNA-directed DNA/RNA polymerase mu  [ProteinName]  5.980085\n",
       "2  DNA-directed RNA polymerase, mitochondrial      [Protein]  5.257301\n",
       "3  DNA-directed RNA polymerase, mitochondrial  [ProteinName]  5.257301\n",
       "4  DNA-directed RNA polymerase, mitochondrial  [ProteinName]  5.257301\n",
       "5               DNA/RNA-binding protein KIN17  [ProteinName]  5.257301\n",
       "6               DNA/RNA-binding protein KIN17      [Protein]  5.257301\n",
       "7  DNA-directed RNA polymerase, mitochondrial      [Protein]  5.257301\n",
       "8                                    pdb:4QIW    [Structure]  4.875343\n",
       "9                                    pdb:6KF3    [Structure]  4.851152"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find matches that contain the terms DNA and RNA\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('bioentities', 'DNA AND RNA') YIELD node, score\n",
    "RETURN node.name AS name, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Keyword Query for Geographic Ids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 1\n"
     ]
    },
    {
     "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>name</th>\n",
       "      <th>node.placeName</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>United States</td>\n",
       "      <td>None</td>\n",
       "      <td>[Location, Country]</td>\n",
       "      <td>2.330875</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            name node.placeName         labels(node)     score\n",
       "0  United States           None  [Location, Country]  2.330875"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find matches for the id \"USA\" (iso3 country code)\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('geoids', 'USA') YIELD node, score\n",
    "RETURN node.name AS name, node.placeName, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 3\n"
     ]
    },
    {
     "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>name</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Canada</td>\n",
       "      <td>[Location, Country]</td>\n",
       "      <td>7.894792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>California</td>\n",
       "      <td>[Location, Admin1]</td>\n",
       "      <td>3.345964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Capellen</td>\n",
       "      <td>[Location, Admin1]</td>\n",
       "      <td>3.345964</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name         labels(node)     score\n",
       "0      Canada  [Location, Country]  7.894792\n",
       "1  California   [Location, Admin1]  3.345964\n",
       "2    Capellen   [Location, Admin1]  3.345964"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find matches for the id \"CA\"\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('geoids', 'CA') YIELD node, score\n",
    "RETURN node.name AS name, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 1\n"
     ]
    },
    {
     "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>name</th>\n",
       "      <th>node.placeName</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>90210</td>\n",
       "      <td>Beverly Hills</td>\n",
       "      <td>[Location, PostalCode]</td>\n",
       "      <td>5.563916</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name node.placeName            labels(node)     score\n",
       "0  90210  Beverly Hills  [Location, PostalCode]  5.563916"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find matches that contain the ZIP code 90210\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('geoids', '90210') YIELD node, score\n",
    "RETURN node.name AS name, node.placeName, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 35\n"
     ]
    },
    {
     "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>name</th>\n",
       "      <th>node.fips</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bokak Atoll</td>\n",
       "      <td>None</td>\n",
       "      <td>[Location, Admin1]</td>\n",
       "      <td>3.345964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jayuya</td>\n",
       "      <td>None</td>\n",
       "      <td>[Location, Admin1]</td>\n",
       "      <td>3.345964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Pondera County</td>\n",
       "      <td>073</td>\n",
       "      <td>[Location, Admin2]</td>\n",
       "      <td>2.655782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Owyhee County</td>\n",
       "      <td>073</td>\n",
       "      <td>[Location, Admin2]</td>\n",
       "      <td>2.655782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lincoln County</td>\n",
       "      <td>073</td>\n",
       "      <td>[Location, Admin2]</td>\n",
       "      <td>2.655782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>San Diego County</td>\n",
       "      <td>073</td>\n",
       "      <td>[Location, Admin2]</td>\n",
       "      <td>2.655782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Marathon County</td>\n",
       "      <td>073</td>\n",
       "      <td>[Location, Admin2]</td>\n",
       "      <td>2.655782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Jerauld County</td>\n",
       "      <td>073</td>\n",
       "      <td>[Location, Admin2]</td>\n",
       "      <td>2.655782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Lawrence County</td>\n",
       "      <td>073</td>\n",
       "      <td>[Location, Admin2]</td>\n",
       "      <td>2.655782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Orleans County</td>\n",
       "      <td>073</td>\n",
       "      <td>[Location, Admin2]</td>\n",
       "      <td>2.655782</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               name node.fips        labels(node)     score\n",
       "0       Bokak Atoll      None  [Location, Admin1]  3.345964\n",
       "1            Jayuya      None  [Location, Admin1]  3.345964\n",
       "2    Pondera County       073  [Location, Admin2]  2.655782\n",
       "3     Owyhee County       073  [Location, Admin2]  2.655782\n",
       "4    Lincoln County       073  [Location, Admin2]  2.655782\n",
       "5  San Diego County       073  [Location, Admin2]  2.655782\n",
       "6   Marathon County       073  [Location, Admin2]  2.655782\n",
       "7    Jerauld County       073  [Location, Admin2]  2.655782\n",
       "8   Lawrence County       073  [Location, Admin2]  2.655782\n",
       "9    Orleans County       073  [Location, Admin2]  2.655782"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find matches that contain the county FIPS code 073\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('geoids', '073') YIELD node, score\n",
    "RETURN node.name AS name, node.fips, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Range Query\n",
    "Range Queries allow one to match documents whose field(s) values are between the lower and upper bound specified by the Range Query. Range Queries can be inclusive or exclusive of the upper and lower bounds. Inclusive range queries are denoted by square brackets `[ ]`. Exclusive range queries are denoted by curly brackets `{ }`. Sorting is done lexicographically."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 25\n"
     ]
    },
    {
     "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>name</th>\n",
       "      <th>node.placeName</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>90201</td>\n",
       "      <td>Bell Gardens</td>\n",
       "      <td>[Location, PostalCode]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>90233</td>\n",
       "      <td>Culver City</td>\n",
       "      <td>[Location, PostalCode]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>90250</td>\n",
       "      <td>Hawthorne</td>\n",
       "      <td>[Location, PostalCode]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>90249</td>\n",
       "      <td>Gardena</td>\n",
       "      <td>[Location, PostalCode]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>90248</td>\n",
       "      <td>Gardena</td>\n",
       "      <td>[Location, PostalCode]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name node.placeName            labels(node)  score\n",
       "0  90201   Bell Gardens  [Location, PostalCode]    1.0\n",
       "1  90233    Culver City  [Location, PostalCode]    1.0\n",
       "2  90250      Hawthorne  [Location, PostalCode]    1.0\n",
       "3  90249        Gardena  [Location, PostalCode]    1.0\n",
       "4  90248        Gardena  [Location, PostalCode]    1.0"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find matches that contain the ZIP range 90200 to 90250\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('geoids', 'name: [90200 TO 90250]') YIELD node, score\n",
    "RETURN node.name AS name, node.placeName, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Protein Sequence Query\n",
    "**NOTE: The Lucence full-text search indexes only the first 255 characters.** Sequences longer than 255 residues will be truncated to 255 characters and only the first 255 characters will be used in the query."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 1\n"
     ]
    },
    {
     "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>name</th>\n",
       "      <th>node.accession</th>\n",
       "      <th>node.taxonomyId</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Non-structural protein 11</td>\n",
       "      <td>uniprot:P0DTC1</td>\n",
       "      <td>taxonomy:2697049</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>5.965485</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        name  node.accession   node.taxonomyId labels(node)  \\\n",
       "0  Non-structural protein 11  uniprot:P0DTC1  taxonomy:2697049    [Protein]   \n",
       "\n",
       "      score  \n",
       "0  5.965485  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find matches that contain the sequence: SADAQSFLNGFAV\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('sequences', 'SADAQSFLNGFAV') YIELD node, score\n",
    "RETURN node.name AS name, node.accession, node.taxonomyId, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Regular Expression Query\n",
    "Lucene supports a limited number of queries with regular expressions ([RegExp](https://lucene.apache.org/core/5_5_0/core/org/apache/lucene/util/automaton/RegExp.html)). Regular expressions are enclosed between two forward slashes `/regular expression/`. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Matching variable characters\n",
    "A `.` specifies a variable character in a term."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 2\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        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>name</th>\n",
       "      <th>node.sequence</th>\n",
       "      <th>node.accession</th>\n",
       "      <th>node.taxonomyId</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Non-structural protein 11</td>\n",
       "      <td>SADAQSFLNGFAV</td>\n",
       "      <td>uniprot:P0DTC1</td>\n",
       "      <td>taxonomy:2697049</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Non-structural protein 11</td>\n",
       "      <td>SADASTFLNGFAV</td>\n",
       "      <td>uniprot:P0C6U8</td>\n",
       "      <td>taxonomy:694009</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        name  node.sequence  node.accession   node.taxonomyId  \\\n",
       "0  Non-structural protein 11  SADAQSFLNGFAV  uniprot:P0DTC1  taxonomy:2697049   \n",
       "1  Non-structural protein 11  SADASTFLNGFAV  uniprot:P0C6U8   taxonomy:694009   \n",
       "\n",
       "  labels(node)  score  \n",
       "0    [Protein]    1.0  \n",
       "1    [Protein]    1.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find matches for the sequence SADA..FLNGFAV with two variable residues.\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('sequences', '/SADA..FLNGFAV/') YIELD node, score\n",
    "RETURN node.name AS name, node.sequence, node.accession, node.taxonomyId, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Matching alternative characters\n",
    "A list of alternative characters can be specified in brackets `[ ]`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 2\n"
     ]
    },
    {
     "data": {
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       "      <th>name</th>\n",
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       "      <th>node.taxonomyId</th>\n",
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       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Non-structural protein 11</td>\n",
       "      <td>SADAQSFLNGFAV</td>\n",
       "      <td>uniprot:P0DTC1</td>\n",
       "      <td>taxonomy:2697049</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Non-structural protein 11</td>\n",
       "      <td>SADASTFLNGFAV</td>\n",
       "      <td>uniprot:P0C6U8</td>\n",
       "      <td>taxonomy:694009</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        name  node.sequence  node.accession   node.taxonomyId  \\\n",
       "0  Non-structural protein 11  SADAQSFLNGFAV  uniprot:P0DTC1  taxonomy:2697049   \n",
       "1  Non-structural protein 11  SADASTFLNGFAV  uniprot:P0C6U8   taxonomy:694009   \n",
       "\n",
       "  labels(node)  score  \n",
       "0    [Protein]    1.0  \n",
       "1    [Protein]    1.0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find matches that contain sequences with alternative residues Q or S at position 4 and S or T\n",
    "# at position 5 (zero-based positions)\n",
    "\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('sequences', '/SADA[QS][ST]FLNGFAV/') YIELD node, score\n",
    "RETURN node.name AS name, node.sequence, node.accession, node.taxonomyId, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Matching an expression with multiple occurances"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The number of occurances of an expression can be specified:\n",
    "\n",
    "`?` (zero or one occurrence) </br>\n",
    "`*` (zero or more occurrences) </br>\n",
    "`+` (one or more occurrences) </br>\n",
    "`{n}` (n occurrences) </br>\n",
    "`{n,}` (n or more occurrences) </br>\n",
    "`{n,m}` (n to m occurrences, including both) </br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 4\n"
     ]
    },
    {
     "data": {
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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>name</th>\n",
       "      <th>node.sequence</th>\n",
       "      <th>node.accession</th>\n",
       "      <th>node.taxonomyId</th>\n",
       "      <th>labels(node)</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Replicase polyprotein 1ab</td>\n",
       "      <td>MESLVPGFNEKTHVQLSLPVLQVRDVLVRGFGDSVEEVLSEARQHL...</td>\n",
       "      <td>uniprot:P0DTD1</td>\n",
       "      <td>taxonomy:2697049</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Helicase</td>\n",
       "      <td>AVGACVLCNSQTSLRCGACIRRPFLCCKCCYDHVISTSHKLVLSVN...</td>\n",
       "      <td>uniprot:P0C6X7</td>\n",
       "      <td>taxonomy:694009</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Replicase polyprotein 1ab</td>\n",
       "      <td>MESLVLGVNEKTHVQLSLPVLQVRDVLVRGFGDSVEEALSEAREHL...</td>\n",
       "      <td>uniprot:P0C6X7</td>\n",
       "      <td>taxonomy:694009</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Helicase</td>\n",
       "      <td>AVGACVLCNSQTSLRCGACIRRPFLCCKCCYDHVISTSHKLVLSVN...</td>\n",
       "      <td>uniprot:P0DTD1</td>\n",
       "      <td>taxonomy:2697049</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        name  \\\n",
       "0  Replicase polyprotein 1ab   \n",
       "1                   Helicase   \n",
       "2  Replicase polyprotein 1ab   \n",
       "3                   Helicase   \n",
       "\n",
       "                                       node.sequence  node.accession  \\\n",
       "0  MESLVPGFNEKTHVQLSLPVLQVRDVLVRGFGDSVEEVLSEARQHL...  uniprot:P0DTD1   \n",
       "1  AVGACVLCNSQTSLRCGACIRRPFLCCKCCYDHVISTSHKLVLSVN...  uniprot:P0C6X7   \n",
       "2  MESLVLGVNEKTHVQLSLPVLQVRDVLVRGFGDSVEEALSEAREHL...  uniprot:P0C6X7   \n",
       "3  AVGACVLCNSQTSLRCGACIRRPFLCCKCCYDHVISTSHKLVLSVN...  uniprot:P0DTD1   \n",
       "\n",
       "    node.taxonomyId labels(node)  score  \n",
       "0  taxonomy:2697049    [Protein]    1.0  \n",
       "1   taxonomy:694009    [Protein]    1.0  \n",
       "2   taxonomy:694009    [Protein]    1.0  \n",
       "3  taxonomy:2697049    [Protein]    1.0  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This query searches for the subsequence AVGACVLCNSQTSLR by specifiying zero or more variable characters \n",
    "# at the beginning and end of a string.\n",
    "\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('sequences', '/.*AVGACVLCNSQTSLR.*/') YIELD node, score\n",
    "RETURN node.name AS name, node.sequence, node.accession, node.taxonomyId, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 4\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",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>node.sequence</th>\n",
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       "      <th>node.taxonomyId</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Replicase polyprotein 1a</td>\n",
       "      <td>MESLVPGFNEKTHVQLSLPVLQVRDVLVRGFGDSVEEVLSEARQHL...</td>\n",
       "      <td>uniprot:P0DTC1</td>\n",
       "      <td>taxonomy:2697049</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Non-structural protein 11</td>\n",
       "      <td>SADASTFLNGFAV</td>\n",
       "      <td>uniprot:P0C6U8</td>\n",
       "      <td>taxonomy:694009</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Replicase polyprotein 1a</td>\n",
       "      <td>MESLVLGVNEKTHVQLSLPVLQVRDVLVRGFGDSVEEALSEAREHL...</td>\n",
       "      <td>uniprot:P0C6U8</td>\n",
       "      <td>taxonomy:694009</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Non-structural protein 11</td>\n",
       "      <td>SADAQSFLNGFAV</td>\n",
       "      <td>uniprot:P0DTC1</td>\n",
       "      <td>taxonomy:2697049</td>\n",
       "      <td>[Protein]</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        name  \\\n",
       "0   Replicase polyprotein 1a   \n",
       "1  Non-structural protein 11   \n",
       "2   Replicase polyprotein 1a   \n",
       "3  Non-structural protein 11   \n",
       "\n",
       "                                       node.sequence  node.accession  \\\n",
       "0  MESLVPGFNEKTHVQLSLPVLQVRDVLVRGFGDSVEEVLSEARQHL...  uniprot:P0DTC1   \n",
       "1                                      SADASTFLNGFAV  uniprot:P0C6U8   \n",
       "2  MESLVLGVNEKTHVQLSLPVLQVRDVLVRGFGDSVEEALSEAREHL...  uniprot:P0C6U8   \n",
       "3                                      SADAQSFLNGFAV  uniprot:P0DTC1   \n",
       "\n",
       "    node.taxonomyId labels(node)  score  \n",
       "0  taxonomy:2697049    [Protein]    1.0  \n",
       "1   taxonomy:694009    [Protein]    1.0  \n",
       "2   taxonomy:694009    [Protein]    1.0  \n",
       "3  taxonomy:2697049    [Protein]    1.0  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This query specifies zero or more variable characters at the beginning and end of an expression.\n",
    "\n",
    "query = \"\"\"\n",
    "CALL db.index.fulltext.queryNodes('sequences', '/.*SADA[QS][ST]FLNGFAV.*/') YIELD node, score\n",
    "RETURN node.name AS name, node.sequence, node.accession, node.taxonomyId, labels(node), score\n",
    "\"\"\"\n",
    "df = graph.run(query).to_data_frame()\n",
    "print('Results:', df.shape[0])\n",
    "df.head()"
   ]
  }
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