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 "cells": [
  {
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   "source": [
    "# ENTRNA - a framework to predict RNA foldability"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Su, C., Weir, J. D., Zhang, F., Yan, H., & Wu, T. (2019).  \n",
    "**ENTRNA: a framework to predict RNA foldability.**  \n",
    "BMC Bioinformatics, 20(1), 1–11. http://doi.org/10.1186/s12859-019-2948-5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from rna_tools.Seq import RNASequence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "free energy: -27.200000\n",
      "foldability: 0.828365\n"
     ]
    }
   ],
   "source": [
    "seq = 'acucggcuaggcgaguauaaauagccgucaggccuagcgcguccaagccuagccccuucuggggcugggcgaagggucggg'\n",
    "ss =  '((((........)))).......((((..............(((((((((((((((....)))))))))))))))..))))'\n",
    "\n",
    "seq = RNASequence(seq)\n",
    "seq.ss = ss\n",
    "fe = seq.eval()\n",
    "print('free energy: %f' % fe)\n",
    "fa = seq.get_foldability()\n",
    "print('foldability: %f' % fa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "free energy: -11.800000\n",
      "[17, 16, 15, 14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 3, 2, 1, 0, 0, 0, 0, 0, 0, 0, 81, 80, 79, 78, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 75, 74, 73, 72, 71, 70, 69, 68, 67, 66, 65, 64, 63, 62, 61, 0, 0, 0, 0, 56, 55, 54, 53, 52, 51, 50, 49, 48, 47, 46, 45, 44, 43, 42, 0, 0, 28, 27, 26, 25]\n",
      "cd /Users/magnus/work/evoClustRNA/rna-foldability/ENTRNA/ && python -W ignore ENTRNA_predict.py --seq_file /var/folders/yc/ssr9692s5fzf7k165grnhpk80000gp/T/tmpIARsa2 --str_file /var/folders/yc/ssr9692s5fzf7k165grnhpk80000gp/T/tmpfGmLP4\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "===============================================================\n",
      "\n",
      "\n",
      "RNA sequence:\n",
      "acucggcuaggcgaguauaaauagccgucaggccuagcgcguccaagccuagccccuucuggggcugggcgaagggucggg\n",
      "RNA secondary structure:\n",
      "[17, 16, 15, 14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 3, 2, 1, 0, 0, 0, 0, 0, 0, 0, 81, 80, 79, 78, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 75, 74, 73, 72, 71, 70, 69, 68, 67, 66, 65, 64, 63, 62, 61, 0, 0, 0, 0, 56, 55, 54, 53, 52, 51, 50, 49, 48, 47, 46, 45, 44, 43, 42, 0, 0, 28, 27, 26, 25]\n",
      "This is pseudoknot-free RNA\n",
      "Foldability: 0.8283652197473068\n",
      "\n",
      "\n",
      "===============================================================\n",
      "\n",
      "\n",
      "\n",
      "foldability: 0.828365\n"
     ]
    }
   ],
   "source": [
    "seq = 'acucggcuaggcgaguauaaauagccgucaggccuagcgcguccaagccuagccccuucuggggcugggcgaagggucggg'\n",
    "ss =  '((((..[[[[[..)))).......((((....]]]]]....(((((((((((((((....)))))))))))))))..))))'\n",
    "\n",
    "seq = RNASequence(seq)\n",
    "seq.ss = ss\n",
    "fe = seq.eval()\n",
    "print('free energy: %f' % fe)\n",
    "fa = seq.get_foldability(verbose=True)\n",
    "print('foldability: %f' % fa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "free energy: -13.500000\n",
      "foldability: 0.055185\n"
     ]
    }
   ],
   "source": [
    "seq = RNASequence(\"GGCAGGGGCGCUUCGGCCCCCUAUGCC\")\n",
    "seq.ss =          \"((((((((.((....)).)))).))))\"\n",
    "\n",
    "fe = seq.eval()\n",
    "print('free energy: %f' % fe)\n",
    "fa = seq.get_foldability()\n",
    "print('foldability: %f' % fa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "free energy: 100000.500000\n"
     ]
    }
   ],
   "source": [
    "seq = RNASequence(\"GGCAGGGGCGCUUCGGCCCCCUAUGCC\")\n",
    "ss =              \"..............()...........\"\n",
    "fe = seq.eval(ss=ss)\n",
    "print('free energy: %f' % fe)"
   ]
  }
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