process_uniprot.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "05de48f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "proteins = []\n",
    "proteins_path = \"C:\\\\Users\\\\60553\\\\Downloads\\\\Diease-related Proteins, ChatGPT.csv\"\n",
    "with open(proteins_path, 'r', newline='',encoding = 'utf-8') as f:\n",
    "\n",
    "\n",
    "    rows = csv.reader(_.replace('\\x00', '') for _ in f)\n",
    "    next(rows)\n",
    "\n",
    "    # Get Column names\n",
    "    keys = next(rows)\n",
    "    # Add values by column\n",
    "    for row in rows:\n",
    "        if row[4] != \"\":\n",
    "            proteins.append(row[4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ca6db174",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "211"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(proteins)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "83b2abcf",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import json\n",
    "import os\n",
    "\n",
    "data_dir = \"D:\\\\PyCharm\\\\pythonProject\\\\Sciwing\\\\AI4BioMed\\\\data\\\\\"\n",
    "def download_protein(uniprot_entry):\n",
    "    if os.path.exists(data_dir + f\"{uniprot_entry}.json\"):\n",
    "        print(f\"{uniprot_entry} Existed.\")\n",
    "        return\n",
    "    url = f\"https://www.uniprot.org/uniprot/{uniprot_entry}.json\"\n",
    "    response = requests.get(url)\n",
    "    data = response.json()\n",
    "    with open(data_dir + f\"{uniprot_entry}.json\",\"w\") as f:\n",
    "        data = json.dumps(data)\n",
    "        f.write(data)\n",
    "    print(f\"{uniprot_entry}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "19c9c2a7",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P00747 Existed.\n",
      "P15692 Existed.\n",
      "P14780 Existed.\n",
      "P01375 Existed.\n",
      "Q99836 Existed.\n",
      "P01033 Existed.\n",
      "P09429 Existed.\n",
      "P06702 Existed.\n",
      "P49913 Existed.\n",
      "P01033 Existed.\n",
      "P35916 Existed.\n",
      "O14672 Existed.\n",
      "P35968 Existed.\n",
      "O15263 Existed.\n",
      "O15263 Existed.\n",
      "Q15109 Existed.\n",
      "O95831 Existed.\n",
      "P03950 Existed.\n",
      "P59666 Existed.\n",
      "O00622 Existed.\n",
      "Q9Y275 Existed.\n",
      "P06213 Existed.\n",
      "P15692 Existed.\n",
      "P61073 Existed.\n",
      "Q12866 Existed.\n",
      "P19320 Existed.\n",
      "P08631 Existed.\n",
      "P14780 Existed.\n",
      "O43927 Existed.\n",
      "P22894 Existed.\n",
      "P09429 Existed.\n",
      "P49238 Existed.\n",
      "P08253 Existed.\n",
      "P00797 Existed.\n",
      "P19320 Existed.\n",
      "P14735 Existed.\n",
      "P03973 Existed.\n",
      "P08253 Existed.\n",
      "P58753 Existed.\n",
      "P39059 Existed.\n",
      "Q02763 Existed.\n",
      "Q9NRM6 Existed.\n",
      "Q8WTQ1 Existed.\n",
      "O00622 Existed.\n",
      "Q16552 Existed.\n",
      "P01116 Existed.\n",
      "P09238 Existed.\n",
      "P01024 Existed.\n",
      "P27986 Existed.\n",
      "Q13686 Existed.\n",
      "P09455 Existed.\n",
      "P05154 Existed.\n",
      "P29508 Existed.\n",
      "O14672 Existed.\n",
      "Q92583 Existed.\n",
      "P98155 Existed.\n",
      "P24821 Existed.\n",
      "P23297 Existed.\n",
      "O00258 Existed.\n",
      "O15382 Existed.\n",
      "P29692 Existed.\n",
      "Q9Y243 Existed.\n",
      "Q9GZX6 Existed.\n",
      "P01579 Existed.\n",
      "P01579 Existed.\n",
      "P04156 Existed.\n",
      "P28066 Existed.\n",
      "P01263 Existed.\n",
      "P02741 Existed.\n",
      "P02741 Existed.\n",
      "P01133 Existed.\n",
      "P02741 Existed.\n",
      "P35398 Existed.\n",
      "P07948 Existed.\n",
      "P02788 Existed.\n",
      "Q9Y6C2 Existed.\n",
      "Q8WUI4 Existed.\n",
      "Q16621 Existed.\n",
      "P01579 Existed.\n",
      "P41159 Existed.\n",
      "Q99523 Existed.\n",
      "P10912 Existed.\n",
      "Q14863 Existed.\n",
      "P37840 Existed.\n",
      "Q14118 Existed.\n",
      "Q16539 Existed.\n",
      "P08100 Existed.\n",
      "Q16539 Existed.\n",
      "P04156 Existed.\n",
      "Q9NR71 Existed.\n",
      "P60866 Existed.\n",
      "Q9Y2R2 Existed.\n",
      "Q9UMF0 Existed.\n",
      "P59665 Existed.\n",
      "Q6P1J9 Existed.\n",
      "P02686 Existed.\n",
      "Q96GM5 Existed.\n",
      "P01160 Existed.\n",
      "Q9C000 Existed.\n",
      "Q9H9S0 Existed.\n",
      "P29508 Existed.\n",
      "P04792 Existed.\n",
      "Q8TE69 Existed.\n",
      "P02745 Existed.\n",
      "P01031 Existed.\n",
      "POU5F1B Existed.\n",
      "P27105 Existed.\n",
      "POU5F1B Existed.\n",
      "P50613 Existed.\n",
      "Q06187 Existed.\n",
      "P32119 Existed.\n",
      "Q9NVW2 Existed.\n",
      "P06756 Existed.\n",
      "P24522 Existed.\n",
      "Q9NP58 Existed.\n",
      "Q5S007 Existed.\n",
      "P48067 Existed.\n",
      "P01579 Existed.\n",
      "O15162 Existed.\n",
      "Q16539 Existed.\n",
      "Q02763 Existed.\n",
      "Q8IXJ6 Existed.\n",
      "P52306 Existed.\n",
      "P09238 Existed.\n",
      "P04629 Existed.\n",
      "Q7Z5W3 Existed.\n",
      "P01210 Existed.\n",
      "Q15070 Existed.\n",
      "Q8WTQ1 Existed.\n",
      "Q8IYX4 Existed.\n",
      "Q8WXB1 Existed.\n",
      "P04792 Existed.\n",
      "P04792 Existed.\n",
      "P48061 Existed.\n",
      "P13473 Existed.\n",
      "O43897 Existed.\n",
      "Q8WYQ5 Existed.\n",
      "Q96EQ8 Existed.\n",
      "Q8NDV7 Existed.\n",
      "P01579 Existed.\n",
      "P27986 Existed.\n",
      "P06213 Existed.\n",
      "O75173 Existed.\n",
      "Q9NRR4 Existed.\n",
      "Q86U44 Existed.\n",
      "Q7Z699 Existed.\n",
      "Q07817 Existed.\n",
      "P46108 Existed.\n",
      "P46108 Existed.\n",
      "O75530 Existed.\n",
      "O43524 Existed.\n",
      "Q13619 Existed.\n",
      "P01344 Existed.\n",
      "P14735 Existed.\n",
      "Q14289 Existed.\n",
      "P01130 Existed.\n",
      "P19838 Existed.\n",
      "O00329 Existed.\n",
      "Q12792 Existed.\n",
      "Q05066 Existed.\n",
      "Q02763 Existed.\n",
      "Q13118 Existed.\n",
      "Q9UP95 Existed.\n",
      "Q76LX8 Existed.\n",
      "O60784 Existed.\n",
      "P53350 Existed.\n",
      "P53350 Existed.\n",
      "Q6IBS0 Existed.\n",
      "Q8IXJ6 Existed.\n",
      "Q00169 Existed.\n",
      "Q02078 Existed.\n",
      "Q9NZQ0 Existed.\n",
      "Q7Z699 Existed.\n",
      "P07948 Existed.\n",
      "Q9H3D4 Existed.\n",
      "P78363 Existed.\n",
      "P24941 Existed.\n",
      "Q8WXH5 Existed.\n",
      "O43236 Existed.\n",
      "O00167 Existed.\n",
      "O60315 Existed.\n",
      "P35226 Existed.\n",
      "Q13950 Existed.\n",
      "Q13485 Existed.\n",
      "Q01094 Existed.\n",
      "P56178 Existed.\n",
      "P24941 Existed.\n",
      "O15392 Existed.\n",
      "Q12959 Existed.\n",
      "Q9Y4K0 Existed.\n",
      "Q14847 Existed.\n",
      "P15692 Existed.\n",
      "Q9ULH1 Existed.\n",
      "P12931 Existed.\n",
      "P50613 Existed.\n",
      "O15198 Existed.\n",
      "P06241 Existed.\n",
      "P50552 Existed.\n",
      "Q16566 Existed.\n",
      "P17948 Existed.\n",
      "Q92630 Existed.\n",
      "P32321 Existed.\n",
      "P48426 Existed.\n",
      "P09914 Existed.\n",
      "P04637 Existed.\n",
      "Q6ZN17 Existed.\n",
      "P08581 Existed.\n",
      "Q9UKV8 Existed.\n",
      "P01100 Existed.\n",
      "P62993 Existed.\n",
      "P45974 Existed.\n"
     ]
    }
   ],
   "source": [
    "for entry in proteins:\n",
    "    download_protein(entry)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4f69737c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_input(protein_entry):\n",
    "\n",
    "    res = {}\n",
    "    with open(data_dir + f\"{protein_entry}.json\",\"r\") as f:\n",
    "        string = f.readlines()[0]\n",
    "        entry = json.loads(string)\n",
    "\n",
    "        comments_text = \"\"\n",
    "        comments_text_with_keys = \"\"\n",
    "        \n",
    "        ref_text = \"\"\n",
    "        uniProtKB_text = \"\"\n",
    "        \n",
    "        input_texts = \"\"\n",
    "        input_texts_with_keys = \"\"\n",
    "        # comments value\n",
    "        active_comments = {\"FUNCTION\":[], \"CATALYTIC ACTIVITY\":[], \"COFACTOR\":[], \"ACTIVITY REGULATION\":[],\n",
    "                       \"TISSUE SPECIFICITY\":[], \"INDUCTION\":[], \"DOMAIN\":[], \"DISEASE\":[]}\n",
    "\n",
    "        if \"comments\" in entry.keys():\n",
    "            comments = entry[\"comments\"]\n",
    "            for comment in comments:\n",
    "                value = \"\"\n",
    "                if \"commentType\" in comment.keys() and comment[\"commentType\"] in active_comments.keys():\n",
    "                    if comment[\"commentType\"] == \"CATALYTIC ACTIVITY\":\n",
    "                        value = comment[\"reaction\"][\"name\"]\n",
    "                    elif comment[\"commentType\"] == \"COFACTOR\":\n",
    "                        if \"note\" in comment.keys():\n",
    "                            value = comment[\"note\"][\"texts\"][0][\"value\"]\n",
    "                    elif comment[\"commentType\"] == \"DISEASE\":\n",
    "                        values = []\n",
    "                        if \"disease\" in comment.keys():\n",
    "                            values.append(comment[\"disease\"][\"description\"])\n",
    "                        if \"note\" in comment.keys():\n",
    "                            values.append(comment[\"note\"][\"texts\"][0][\"value\"])\n",
    "                        value = \" \".join(values)\n",
    "                    else:\n",
    "                        value = comment[\"texts\"][0][\"value\"]\n",
    "                    active_comments[comment[\"commentType\"]].append(value)\n",
    "            for k, v in active_comments.items():\n",
    "                comments_text += \" \".join(v)\n",
    "                t = \" \".join(v)\n",
    "                comments_text_with_keys += (k + \": \" + t)\n",
    "        # references title\n",
    "        if \"references\" in entry.keys():\n",
    "            references = entry[\"references\"]\n",
    "            titles = []\n",
    "            for ref in references:\n",
    "                if \"title\" in ref[\"citation\"].keys():\n",
    "                    titles.append(ref[\"citation\"][\"title\"])\n",
    "            ref_text = \" \".join(titles)\n",
    "\n",
    "        # uniProtKBCrossRef\n",
    "        if \"uniProtKBCrossReferences\" in entry.keys():\n",
    "            uniProt_references = entry[\"uniProtKBCrossReferences\"]\n",
    "            uniProt_des = []\n",
    "            for ref in uniProt_references:\n",
    "                properties = {}\n",
    "                for item in ref[\"properties\"]:\n",
    "                    properties[item[\"key\"]] = item[\"value\"]\n",
    "                if \"Description\" in properties.keys():\n",
    "#                     print(properties[\"Description\"])\n",
    "                    if properties[\"Description\"] != \"-\":\n",
    "                        uniProt_des.append(properties[\"Description\"])\n",
    "            uniProtKB_text = \" \".join(uniProt_des)\n",
    "\n",
    "        # input\n",
    "        input_texts = comments_text + ref_text + uniProtKB_text\n",
    "        res[\"protein\"] = protein_entry\n",
    "        res[\"input_text\"] = input_texts\n",
    "        res[\"input_text_with_keys\"] = comments_text + \"Reference titles: \" + ref_text \n",
    "#         res[\"comments\"] = comments_text\n",
    "#         res[\"ref_titles\"] = ref_text\n",
    "#         res[\"uniProt_description\"] = uniProtKB_text\n",
    "    return res\n",
    "\n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "70968da4",
   "metadata": {},
   "outputs": [],
   "source": [
    "labels = {}\n",
    "with open(proteins_path, 'r', newline='',encoding = 'utf-8') as f:\n",
    "            \n",
    "\n",
    "    rows = csv.reader(_.replace('\\x00', '') for _ in f)\n",
    "    next(rows)\n",
    "\n",
    "    # Get Column names\n",
    "    keys = next(rows)\n",
    "    # Add values by column\n",
    "    for row in rows:\n",
    "        if row[4] != \"\":\n",
    "            label = (row[10], row[11])\n",
    "            labels[row[4]] = label\n",
    "            \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e5cf547f",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = []\n",
    "for i in proteins:\n",
    "    res = get_input(i)\n",
    "    data = res\n",
    "    if i in labels.keys():\n",
    "        data[\"labels\"] = \"Score: \" + labels[i][0] + \".\"\n",
    "        if len(labels[i][1])>1:\n",
    "            data[\"labels\"] += \" Explanation: \" + labels[i][1]\n",
    "        data[\"Score\"] = labels[i][0]\n",
    "        data[\"Explanation\"] = labels[i][1]\n",
    "        dataset.append(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ffc9dcc1",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "save_dir = \"D:/PyCharm/pythonProject/Sciwing/AI4BioMed/\"\n",
    "with open(save_dir + \"uniprot.json\",\"w\") as f:\n",
    "    json.dump(dataset, f, indent = 4)\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fd28d079",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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