0-getting-started.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0ebc72c8-195f-4aed-9efe-7f0d6d77ab91",
   "metadata": {},
   "outputs": [],
   "source": [
    "import dinkum\n",
    "from dinkum.vfg import Gene, Receptor, Ligand\n",
    "from dinkum.vfn import Tissue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "69cca81b-0d32-496d-9b80-90897d2760e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "initializing: dinkum v0.3.2\n"
     ]
    }
   ],
   "source": [
    "dinkum.reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1930a2de-3533-4edc-bd58-756e4a174726",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define a Gene with name 'X', assign it to variable 'x' in Python\n",
    "x = Gene(name='X')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f7903f68-2fb5-4c02-8fac-bb0ce5427b2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define another Gene with name 'Y', assign it to variable 'y' in Python\n",
    "y = Gene(name='Y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "97ca5169-aebd-4508-8135-2970779c702a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a Tissue, and add genes to it.\n",
    "m = Tissue(name='M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "70331923-0efe-4207-8272-3c2a0d2c63c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "start=1 stop=5\n"
     ]
    },
    {
     "data": {
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      "image/png": "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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=160x230>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# run for 5 ticks (1 to 5)\n",
    "dinkum.run_and_display(stop=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c200b6d8-599b-4411-b6af-c86642e242e6",
   "metadata": {},
   "source": [
    "Underwhelming, ehh? All the genes are off because ... we haven't turned any genes on!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9f46fd1b-3108-4a10-80e9-482c9f8422d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# turn 'x' on in tissue m starting at time t\n",
    "x.is_present(where=m, start=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e6e630ef-ae88-46a6-89fe-c5292bd1bde9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "start=1 stop=5\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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fzRq+Jf8AkYLr/gH/AKAKya1vEv8AyMF1/wAA/wDQBWTXxp+nhXV+C/8Al+/7Z/8As1cpXV+C/wDl+/7Z/wDs1AHV0UUUAFFFFABRRRQAUUUUAFFFFABRRRQBh+IvDv8Ab/2b/SvI8jd/yz3bt2PcelYX/Cuv+or/AOS//wBlXc0V10sdXpRUISsl5I86vlODxFR1asLyfm/8zhv+Fdf9RX/yX/8AsqvaP4L/ALJ1WG+/tDzfK3fJ5O3OVI67j611dFOWYYmcXGUtH5L/ACIp5Ngac1OMNU7rV9Pmc/qXhj+0dQluvtnl+Zj5fKzjAA659qqf8IX/ANRD/wAg/wD2VdXRXGeocp/whf8A1EP/ACD/APZVraLov9j+f/pHnebt/g24xn3PrWrRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAHL3vimXTvG0umXSwppcemLdGbB3iUmU7c5xjy4XPTPB5q54Q1a/1vw3De6nDFBemaeKWOEEKpjmePHJJ6IM+9Jq/hPT9au5rm5kuFeVIEYRsANsTSnHIPDCaRW9VPGOtaWm6dDpdq9vAzsj3E1wS5BO6WVpGHAHGXOPbHXrQBbooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAP//Z",
      "image/png": "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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=160x230>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# run for 5 ticks (1 to 5)\n",
    "dinkum.run_and_display(stop=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eeecc139-25ac-4751-9091-757f4336ed5c",
   "metadata": {},
   "source": [
    "Better, but still underwhelming - we haven't defined any regulatory relationships! Let's make X a maternal effect gene by turning it on at time t=1, and then have it positively regulate Y."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "105ddeb7-f891-4de9-8843-431813255d0b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "initializing: dinkum v0.3.2\n",
      "start=1 stop=5\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAKAAAADmCAIAAADdrBkLAAAKZUlEQVR4Ae2dS0hVXRTHu2pPyaIIKnAQDorIBIse9ITKG72ECKN3QVGDCqUGQVCziqKCokFB0IsGUZZRAyPqEhVEQQ3UihDCBkEPUMtBofWtD+F8dvVs77K9P9da/h3IOWevs+5//3+uc65w1tmJ379/98OPXQey7E4NM/vXAQA2/ncAwABs3AHj00MFA7BxB4xPDxUMwMYdMD49VDAAG3fA+PRQwQBs3AHj00MFA7BxB4xPDxUMwMYdYEyvurp65cqV7SfU1tZOmzatra2NcX58aF1dXWFh4a9fv9pDpk6dWlNTEx/OGEEFM8xKJpM/f/589OgRnVNRUXHq1Kns7GzG+fGhEydOnDRp0rVr1yjk7t27BQUFtBsfzhmhJzrwk7kDb968mTFjxvXr17du3Zr5WZlEUhETVLokzJo1iy4PmZySSUyCgjh/D4jtV15eXllZ+fLly5EjR/q1Y926dUOGDGlpabl69aqvzDm+EvWdPM3NzTk5Od+/f/cO+MCBA3StplL2aCbuwTwznzx50tTUdPbs2d27d/POzCB6/PjxQ4cOpd8ZxGYaAsCZOkVxra2t9N3q2LFjixYtoiKuqqpinNxLobgHM4w/ceLEly9fDh06ROc0NDTQl+oXL17k5uYyUnQXOnz48MbGxu6iGOMAzDBLYygu0RqpMTQDMMMsjaEArJEaQzMAM8zSGArAGqkxNAMwwyyNoQCskRpDMwAzzNIYCsAaqTE0AzDDLI2hAKyRGkMzADPM0hgKwBqpMTQDMMMsjaEArJEaQzMAM8zSGArAGqkxNAMwwyyNoQCskRpDMwAzzNIYCsAaqTE02wR85MiROA/oodTNmzcPGzYsLsDY8T4HePny5VOmTEkkEsZAxk4nkw41XTHU4UNdndR80KXsjx8/0nGq4C5H7R20+eB7e3/A27dvt2/fHv1pp1KpaNt7A0GUWdqGZcAOr3sGOJFypGQP/Z7/3yntrd//7f/dVllZWZTAcvuoo4Kj+ZvfsAmYXnZBP9SH2fGybJ5llxO0+S16zpw5K1as6HLCfe2gzQqm95i4Qfpt0XR/Vu+O2qzg3vVU1KcDsCgc/sUAsH9PRWUEYFE4/IsBYP+eisoIwKJw+BcDwP49FZURgEXh8C8GgP17KiojAIvC4V8MAPv3VFRGABaFw78YAPbvqaiMACwKh38xAOzfU1EZAVgUDv9iANi/p6IyArAoHP7FALB/T0VlBGBROPyLAWD/nsrKaK8bh2Z0+PDhuHmdP39+9uzZRUVFtBBhXIyl4/0sTSaaS1xv2adPn+bOnUvLx71+/XrChAlRvOENg5fogwcP0rJkJSUlnS+VX79+3blzZ1ZWVn5+Pm13DrB3xHLzmaM36eLFi7SIKF2u7RFNm5FlwGlTjXbr6+tLS0sfPnw4atSo6GAmG4lUJlGZxqC7MFOn4uK6rGC6eq9evZpql0s37lOEH7fZmxTXXUhfpjZt2rRnz57p06cLB+NLnsEvWWRNXHfhhQsX6L8jWjt0/vz5y5Yt82Wi5Dw278GBHNd4D7ZZwYEAa0wLwBqpMTQDMMMsjaEArJEaQzMAM8zSGArAGqkxNAMwwyyNoQCskRpDMwAzzNIYCsAaqTE0AzDDLI2hAKyRGkMzADPM0hgKwBqpMTQDMMMsjaEArJEaQzMAM8zSGArAGqkxNAMwwyyNoQCskRpDMwAzzFIZarLvKq67sKWlhdYUmjdvXnFx8Z07d0zOPW1SNh+bjVv36ujRo9R5tnfvXlrgbubMme/fv1dZlBzRBjsbou7Ce/fupVmxbdu23NxcOlhbW9u/f/+0UZO7liu4y94korhhw4bKysrbt28vWLDAJNSOk7IMuOM807arqqpu3Lhx6dKltOPu3UTKPc4b7dhdGC6z5W/RVMHUgxT9kP27du1qbW2lDWpM6nbxLB4uqdEG78FkdVx3YVNT061bt1atWvX06VNa2VAqFJ+6bF6ily5dSmt80z9CaVY1NDRQ+yjhHzBgwOnTp+k1HWkB7t1wF9KAmenfJvesMBo5EBBDKvoQDxsd7+6W78EerNKfAoD1M3TOAICd9ugfBGD9DJ0zAGCnPfoHAVg/Q+cMANhpj/5BANbP0DkDAHbao38QgPUzdM4AgJ326B8EYP0MnTMAYKc9+gcBWD9D5wwA2GmP/kEA1s/QOQMAdtqjfxCA9TN0zgCAnfboHwRg/QydMwBgpz0GBtOa0WzsxnUXRrOjp94HDRoU7RresPlcdFx3YXtBfvv2LZlM1tTUNDc3GyhR9xQMXqKj7sK4me/bt6+8vJz6SOMCLB23XMFddhc+fvz4+PHjN2/edFe5GcaWAXeG9OPHD2rvp97RsWPH9gBwItU5Zc+PdOw/CJfZZvNZu+udK5haRukGvHbtWgqgRQw3btzI7SDtOc9eOtNmBefl5TU2Nrrvsn2kgm1+0Yhbu7CXqqg3P9ZmBQdyNNydMlxmmxUcCLDGtACskRpDMwAzzNIYCsAaqTE0AzDDLI2hAKyRGkMzADPM0hgKwBqpMTQDMMMsjaEArJEaQzMAM8zSGArAGqkxNAMwwyyNoQCskRpDMwAzzNIYCsAaqTE0AzDDLI2hAKyRGkMzADPM0hgKwBqpMTQDMMMslaEmG+viugtpLbRx48ZRcwP97N+/3+Tc0yZl87HZuIfaL1++TOtT7tixQ2Ut9ki0wUu0o7uQ1qQcM2ZMj4zSepLlCu7cm1RRUUEVXFdXN2LEiJMnTxYUFGjllrFuy81ntLZZKpXqaAWtllVUVHTu3DlqMKSVSB88eNBxtNvtxB/Jug3vJuD/6S7sWxVMCwbn5+dnZ2e3tbWNHj368+fP3UD4c1gjYJsVHLd2IfX2r1mzprS09NmzZ4WFhX/is7lns4Lj1i589+7dli1bcnJy6A0sZ86c4d6DNVawTcCBilEj4KxAXiCtEAcAWAiIUDIAOJSzQvICsBAQoWQAcChnheQFYCEgQskA4FDOCskLwEJAhJIBwKGcFZIXgIWACCUDgEM5KyQvAAsBEUoGAIdyVkheABYCIpQMAA7lrJC8ACwERCgZABzKWSF5AVgIiFAyADiUs0LyArAQEKFkAHAoZ4XkxVOVQkCEkoEKDuWskLwALAREKBkAHMpZIXkBWAiIUDIAOJSzQvICsBAQoWQAcChnheQFYCEgQskA4FDOCskLwEJAhJIBwKGcFZIXgIWACCUDgEM5KyQvAAsBEUoGAIdylpt38ODBZWVl0Vnr16+nI9FujzcAuMfWeT5x4MCB9O5FekMb5aU3xtbX19ORv/8MAP57D71lKC4ufv78OaV79erV5MmTveQFYC82+kmSTCarq6spF/2mbS9JAdiLjX6SlJSU3L9/n3LRW1IXLlzoJSkAe7HRTxJ6yXFWVtaHDx8oXV5enpekAOzFRm9JFi9eTGsN+CpfkgXA3th4SUSvUb1y5cqSJUu8ZKMkeGzWl5NC86CChYLxJQuAfTkpNA8ACwXjSxYA+3JSaB4AFgrGlywA9uWk0DwALBSML1kA7MtJoXkAWCgYX7IA2JeTQvP8A1z/UnHJgQ9mAAAAAElFTkSuQmCC",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=160x230>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dinkum.reset()\n",
    "\n",
    "x = Gene(name='X')\n",
    "y = Gene(name='Y')\n",
    "m = Tissue(name='M')\n",
    "\n",
    "x.is_present(where=m, start=1)\n",
    "\n",
    "# now define a regulatory relationship!\n",
    "y.activated_by(source=x, delay=2)\n",
    "\n",
    "# run for 5 ticks (1 to 5)\n",
    "dinkum.run_and_display(stop=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56ccb725-8f66-4462-a09e-8350d97e6703",
   "metadata": {},
   "source": [
    "Here you can see that Y is activated by X after a delay of 2!\n",
    "\n",
    "So this is kind of the minimum you need for something interesting: you need to two genes; a tissue; a transcriptionally active gene; and a regulatory relationship with the other gene.\n",
    "\n",
    "What kind of regulatory interactions are possible?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b41e365-83ce-4c93-8cac-ac3a155a3dc5",
   "metadata": {},
   "source": [
    "## Cell-autonomous interactions\n",
    "\n",
    "There are many possible gene-gene interactions *within* a cell.\n",
    "\n",
    "We've already seen two - `is_present(where=tissue, start=None, duration=None)` and `activated_by(source, delay=1)`.\n",
    "\n",
    "Here's their description:\n",
    "\n",
    "* `is_present(where=tissue, start=None, duration=None)` - this gene is constitutively \"on\" from tick `start` for duration `duration`.\n",
    "* `activated_by(source, delay=1)` - `source` is an upstream activator that acts at the given delay (in ticks).\n",
    "\n",
    "Here are the remaining cell autonomous gene interactions that we have implemented:\n",
    "\n",
    "* `activated_or(sources=[...], delay=1)` - `sources` is a list of upstream activators, any one of which suffices to activate this gene.\n",
    "* `and_not(activator=..., repressor=..., delay=1)` - `activator` activates unless `repressor` is active.\n",
    "* `activated_by_and(sources=[...], delay=1)` - `sources` is a list of upstream activators, all of which must be present to activate this gene.\n",
    "* `toggle_repressed(tf=..., cofactor=..., delay=1)` - this gene is repressed if `tf` is absent, or if `tf` is present without `cofactor`; it is active if both`tf` and `cofactor` are present."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "267f8a8a-fe60-4925-a3cf-919884411566",
   "metadata": {},
   "source": [
    "## Side note: introducing multiple regulatory influences via lists\n",
    "\n",
    "`activated_or` and `activated_by_and` both take *lists* of genes, as opposed to a single gene; to make a Python list, you enclose the genes in square brackets and separate them with commas, e.g. `[x, y]`. The notation is used as below for `z`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3002b20c-6f8c-4730-994e-7713d6888a73",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "initializing: dinkum v0.3.2\n",
      "start=1 stop=7\n"
     ]
    },
    {
     "data": {
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      "image/png": 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WCOpI6zhbvVCHDaW0RFBHWsfZ6oU6bCilJYI60jrOVi/UYUMpLdG/cj9dgLWJMzEAAAAASUVORK5CYII=",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=190x290>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dinkum.reset()\n",
    "\n",
    "x = Gene(name='X')\n",
    "y = Gene(name='Y')\n",
    "z = Gene(name='Z')\n",
    "m = Tissue(name='M')\n",
    "\n",
    "x.is_present(where=m, start=1, duration=2)\n",
    "y.is_present(where=m, start=4, duration=2)\n",
    "\n",
    "z.activated_or(sources=[x, y])\n",
    "\n",
    "# run for 7 ticks\n",
    "dinkum.run_and_display(stop=7)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f33cf882-e174-4770-bcb3-cc7a0d273b37",
   "metadata": {},
   "source": [
    "## Non-cell-autonomous regulation: interactions across cells/tissues\n",
    "\n",
    "dinkum provides the concept of \"tissues\", which are simply a collection of cells that have the same regulatory state.\n",
    "\n",
    "With multiple tissues, you need to define their neighborhood relationship - who is next to whom? - and, if you want them to cross-regulate, you need to define signaling factors and receptors.\n",
    "\n",
    "dinkum supports basic _ligands_ (signaling molecules) and _receptors_. In the dinkum model, ligands are genes that are transcribed (and so they must be transcriptionally activated in a tissue), and then they turn on corresponding receptors in neighboring tissues that are inherently transcriptional activators. The receptor also must be transcribed, but is does not activate downstream genes until the ligand is present.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "30bef2e6-21a4-45eb-a155-027e1ed17acb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "initializing: dinkum v0.3.2\n",
      "start=1 stop=10\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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",
      "image/png": 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b4R6Px6vVqh/xd7/73f79+xcuXOj/ihEELBVgt1vaONNlO/haJp/P12q1VCrlt9uzZ89XvvIV/zgjCFgqwG63tHERlO3yk3ulUlEvYTzEcrl88803qyf3Xbt2jRs37p577jnllFO8bzlAwFKBxpM7u93S9pkre5S5pY/4yolEQgV6cxmxWGzy5Mn33XffunXrbrjhhs2bNzd/O+hx7P8WG/T0QU6od/efUCwW+z8M+yiTyXhr2FizOQ2Pxb2D0He7uS7YuCfN1WxuZZfD3f8ss3jx4pNOOkn9xr744oubH+rd+63OHY00AXb7SOv4oPfrZrj3Hf7xP8uof0Jz5ZVXqmR/8cUXzzrrrEF1OAEB+QLsdvk9OiIVuhnuyWQynU739vYOML3jjjsWLFig3rYfc8wx999//4Bv+YiAjQLsdhu7FkHNboZ7qVRqaXfaaadt27at5VcMImCpALvd0saZLrvL9AVYHwEEEEAgegHCPXpzrogAAggYFyDcjRNzAQQQQCB6AcI9enOuiAACCBgXINyNE3MBBBBAIHoBwj16c66IAAIIGBcg3I0TcwEEEEAgegHCPXpzrogAAggYFyDcjRNzAQQQQCB6AcI9enOuiAACCBgXINyNE3MBBBBAIHoBwj16c66IAAIIGBcg3I0TcwEEEEAgegHCPXpzrogAAggYFyDcjRNzAQQQQCB6AcI9enOuiAACCBgXINyNE3MBBBBAIHoBwj16c66IAAIIGBcg3I0TcwEEEEAgegHCPXpzrogAAggYFyDcjRNzAQQQQCB6gVi9Xo/+qqavWCgUcrmc/yp9fX1LlizZsWPH0UcfvWrVqkmTJvnPYQQBuwTY7Xb1K7Jq3XxyV9u9peC999577LHHbt++/eabb166dGnLcxhEwC4Bdrtd/YqsWgfDPZ/P12q1VCrlR3zwwQcXLFigxmfPnv3tb3/bfwIjCNglwG63q19RVuvma5l4PF6tViuVSjab9TTL5fL48eN/8IMfbNiw4Utf+tI999xz8skne99ygIClAux2SxtnuuxRpi9wBNdPJBIq0JsLOHjw4Fe/+lU1uHbt2uuvv37Tpk3N3w56HPu/xQY9fZAT6t39JxSLxf4Pwz7KZDLeGjbWbE7DY3HvIPTdbq4LNu5JczWbW9nlcPc/uU+YMOGSSy5Rv7HVrwsXLnTvdzh3NGIF2O0jtvVBN+5muKt/FaN+/M8yM2bM2Lp16/nnn69+nTx5chAK4whYJMBut6hZUZbaFeXFIrtWMplMp9P+yy1btuwXv/iFCvef/vSny5cv95/ACALWCbDbrWtZNAW7+eReKpVa8h1//PFPPPFEy68YRMBSAXa7pY0zXbabT+6m1VgfAQQQEC5AuAtvEOUhgAACOgKEu44acxBAAAHhAoS78AZRHgIIIKAjQLjrqDEHAQQQEC5AuAtvEOUhgAACOgKEu44acxBAAAHhAoS78AZRHgIIIKAjQLjrqDEHAQQQEC5AuAtvEOUhgAACOgKEu44acxBAAAHhAoS78AZRHgIIIKAjQLjrqDEHAQQQEC5AuAtvEOUhgAACOgKEu44acxBAAAHhAoS78AZRHgIIIKAjQLjrqDEHAQQQEC5AuAtvEOUhgAACOgKEu44acxBAAAHhAoS78AZRHgIIIKAjQLjrqDEHAQQQEC4Qq9frwkvUKK9QKORyOf/EK6644r333lPjBw8efOONNz744AP/OYwgYJcAu92ufkVWrZvhHo/Hq9VqG8QVK1a8/fbby5Yta3MOXyFghQC73Yo2RV+kg69l8vl8rVZLpVJBmuoPK7/+9a8XLVoUdALjCNgiwG63pVPR1+nyk3ulUslms55puVxuHG/YsKG3t/e+++7zvuIAAXsFGk/u7HZ7O2iocpfDPYhs+vTpKtkTiUTQCUHjsXLQNzrj9e7+WcVisf/DsI8ymYy3Bis3a3gsLh20fy2jvdvN7Rwbfx+Zq9ncyqNc2uUD7qXls8yLL76ofjNoJPuAxfmIgCgBdruodkgoxs1w7zv8oxLcexXjWff09Nx6663eRw4QsF2A3W57Bw3V32Vo3SO7bDKZTKfT/hr++te//vOf/5w2bZr/K0YQsFSA3W5p40yX7eaTe6lUagl36qmnbt++veVXDCJgqQC73dLGmS7bzSd302qsjwACCAgXINyFN4jyEEAAAR0Bwl1HjTkIIICAcAHCXXiDKA8BBBDQESDcddSYgwACCAgXINyFN4jyEEAAAR0Bwl1HjTkIIICAcAHCXXiDKA8BBBDQESDcddSYgwACCAgXINyFN4jyEEAAAR0Bwl1HjTkIIICAcAHCXXiDKA8BBBDQESDcddSYgwACCAgXINyFN4jyEEAAAR0Bwl1HjTkIIICAcAHCXXiDKA8BBBDQESDcddSYgwACCAgXINyFN4jyEEAAAR0Bwl1HjTkIIICAcAHCXXiDKA8BBBDQESDcddSYgwACCAgXiNXrdeElapRXKBRyuZx/4qZNm374wx+OGTPm0KFDPT09U6ZM8Z/DCAJ2CbDb7epXZNW6Ge7xeLxarfoRTz755C1btnzta1/bvXv33Llzd+3a5T+HEQTsEmC329WvyKp18LVMPp+v1WqpVMqPeNxxx3344YdqXP26f/9+/wmMIGCXALvdrn5FWa3LT+6VSiWbzXqa5XJ5x44dyWTytNNOe/PNNx999NE5c+Z433KAgKUCjSd3drul7TNXtsvh7lebPn364sWLL7vsskceeeSpp55auXKl/5w2I7Fymy87/qre3T+lWCz2fxj2USaT8dZg5WYNj8Wlg6DXMsPc7eZ2Dr+PmvekOY1RLu3yAffif5b585//PG/ePHXapZdeeuONNw44n48I2CvAbre3d4YqdzPc+w7/JBIJ9SqmGU6NPP/88+rNzPbt29VfrjZ/xTEClgqw2y1tnOmy3Qx3Fd/pdLq3t3cA37333qtey6jBWCy2YsWKAd/yEQEbBdjtNnYtgprdDPdSqdTSbvLkyc8++2zLrxhEwFIBdruljTNdtoP/FNI0GesjgAAC8gUId/k9okIEEECgYwHCvWMyJiCAAALyBQh3+T2iQgQQQKBjAcK9YzImIIAAAvIFCHf5PaJCBBBAoGMBwr1jMiYggAAC8gUId/k9okIEEECgYwHCvWMyJiCAAALyBQh3+T2iQgQQQKBjAcK9YzImIIAAAvIFCHf5PaJCBBBAoGMBwr1jMiYggAAC8gUId/k9okIEEECgYwHCvWMyJiCAAALyBQh3+T2iQgQQQKBjAcK9YzImIIAAAvIFCHf5PaJCBBBAoGMBwr1jMiYggAAC8gUId/k9okIEEECgYwHCvWMyJiCAAALyBWL1el1+lZ1WWCgUcrmcf9bf/va3hQsXHjhw4Atf+MIDDzwwYcIE/zmMIGCXALvdrn5FVq2b4R6Px6vVqh9x1qxZKvRnzpy5adOmRx999De/+Y3/HEYQsEuA3W5XvyKr1sHXMvl8vlarpVIpP+LOnTu7u7vVuPp18+bN/hMYQcAuAXa7Xf2KslqXn9wrlUo2m/U0y+WyemZftGjRvHnz1GP797///ZZP9975HCBghUDjyZ3dbkWzoizS5XD3O6p37rfccovK9Dlz5tx9993vv/++/5w2I7Fymy87/qre3T+lWCz2fxj2USaT8dZg5WYNj8Wlg6DXMsPc7eZ2Dr+PmvekOedRLu3yAffif5Z56KGH/vCHP4wePfrNN99cv379gPP5iIC9Aux2e3tnqHI3w73v8E8ikVCvYprhXn755SeffPKSSy5ZtWrVlVde2fwVxwhYKsBut7Rxpst28C9UFVkymUyn0367np6en/3sZ1OmTPn4449vvPFG/wmMIGCdALvdupZFU7CbT+6lUqkl36mnnrpt27aWXzGIgKUC7HZLG2e6bDef3E2rsT4CCCAgXIBwF94gykMAAQR0BAh3HTXmIIAAAsIFCHfhDaI8BBBAQEeAcNdRYw4CCCAgXIBwF94gykMAAQR0BAh3HTXmIIAAAsIFCHfhDaI8BBBAQEeAcNdRYw4CCCAgXIBwF94gykMAAQR0BAh3HTXmIIAAAsIFCHfhDaI8BBBAQEeAcNdRYw4CCCAgXIBwF94gykMAAQR0BAh3HTXmIIAAAsIFCHfhDaI8BBBAQEeAcNdRYw4CCCAgXIBwF94gykMAAQR0BAh3HTXmIIAAAsIFCHfhDaI8BBBAQEeAcNdRYw4CCCAgXCBWr9eFlzhoeYVCIZfLtTytWq0uWbJk/fr1H330kTpB/Tp//vwPPvjgy1/+8urVq8eOHdtyFoMIiBVgt4ttjbTCXHhyV9s9iHXu3LnnnntuLBZrnPCTn/xk2rRp27ZtSyaTd911V9AsxhEQK8BuF9sacYWpJ3erf370ox8dddRRs2bNankXe/bsUePqCb3x7de//vV//OMf6vjdd98988wzG4P8ioAtAux2WzoloU4XXsvE43H1+qVSqWSzWe8/nuVy2TtunKA+jh8/fu/evV1dXX19fSeccML777/vncMBAlYIsNutaJOEIkdJKCKUGhKJRHOgh7LmgEVi5QEDw/pY7+6fXiwW+z8M+yiTyXhrsHKzhsdi+0EEu93czuH3UfOeNOfsTri3eXL3fidPmDDhvffeO/HEE9XrGnXsjXOAgF0C7Ha7+nVEqnUh3NU7FvUzlGeZiy666OGHH77lllvUr+r4iIhzUQSGI8BuH47eiJrrwr+WUf/0JZ1OD6Vtt99++9atW6dOnfrcc8/ddtttQ5nCOQiIEmC3i2qH5GJceHIvlUrtidVftzZOUP9s5rHHHmt/Mt8iIFmA3S65O6Jqc+HJXRQoxSCAAAISBAh3CV2gBgQQQCBkAcI9ZFCWQwABBCQIEO4SukANCCCAQMgChHvIoCyHAAIISBAg3CV0gRoQQACBkAUI95BBWQ4BBBCQIEC4S+gCNSCAAAIhCxDuIYOyHAIIICBBgHCX0AVqQAABBEIWINxDBmU5BBBAQIIA4S6hC9SAAAIIhCxAuIcMynIIIICABAHCXUIXqAEBBBAIWYBwDxmU5RBAAAEJAoS7hC5QAwIIIBCyAOEeMijLIYAAAhIECHcJXaAGBBBAIGQBwj1kUJZDAAEEJAgQ7hK6QA0IIIBAyAKEe8igLIcAAghIEIjV63UJdVADAggggECIAjy5h4jJUggggIAUAcJdSieoAwEEEAhRgHAPEZOlEEAAASkChLuUTlAHAgggEKIA4R4iJkshgAACUgQIdymdoA4EEEAgRAHCPURMlkIAAQSkCBDuUjpBHQgggECIAoR7iJgshQACCEgRINyldII6EEAAgRAFCPcQMVkKAQQQkCJAuEvpBHUggAACIQoQ7iFishQCCCAgRYBwl9IJ6kAAAQRCFCDcQ8R0YanPfvazmUzGu5Orr75ajXgfOUDAJQG1t88//3zvjuLxuHfswAHh7kATw7yFMWPGVCqVTz/9VC2q/rf+d+/erUbCvABrISBGQO3tQ4cOlctlMRWFWQjhHqamG2udc845O3bsUPeyc+fOs88+242b4i4QaCnw4x//OJ/Pt/zK9kHC3fYOhl//BRdcsHHjRrWu+lUdh38BVkRAjMCMGTNULVu2bBFTUWiFEO6hUTqzUCqV+tOf/qRuZ/Pmzd/97neduS9uBIGWAq4+vBPuLds9ogfHjRvX1dX1zjvvKIUvfvGLI9qCmx8BAt3d3UcddZR6lHHsXkc5dj/cTigCF1544e23385jeyiYLCJfQD28qw0vv86OKuTJvSOukXLy7Nmzf//731900UUj5Ya5z5EtMG3atNGjRx84cMAlhpj6524u3Q/3ggACCCCgBHhyZxsggAACDgoQ7g42lVtCAAEECHf2AAIIIOCgAOHuYFO5JQQQQIBwZw8ggAACDgoQ7g42lVtCAAEECHf2AAIIIOCgAOHuYFO5JQQQQIBwZw8ggAACDgoQ7g42lVtCAAEE/gtXudG/HXCVlwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=500x380>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dinkum.reset()\n",
    "\n",
    "# create two tissues                                                               \n",
    "m = Tissue(name='M')\n",
    "n = Tissue(name='N')\n",
    "\n",
    "# make them neighbors.                                                          \n",
    "m.add_neighbor(neighbor=n)\n",
    "n.add_neighbor(neighbor=m)\n",
    "\n",
    "a = Gene(name='A')          # permanent positive input in M and N; will turn on receptor R                                                                             \n",
    "m.add_gene(gene=a, start=1)\n",
    "b = Gene(name='B')          # permanent positive input in M and N; will turn on receptor R                                                                             \n",
    "n.add_gene(gene=b, start=1)\n",
    "\n",
    "# VFG:                                                                      \n",
    "l = Ligand(name='L')                       # ligand                                   \n",
    "r = Receptor(name='R', ligand=l)           # receptor with associated ligand                                  \n",
    "y = Gene(name='Y')                         # output         \n",
    "\n",
    "# ligand L: on in tissue M\n",
    "l.is_present(where=m, start=1, duration=6)\n",
    "\n",
    "# receptor R: transcribed by A, activated by ligand L.\n",
    "r.activated_or(sources=[a, b])\n",
    "\n",
    "# gene Y turned on by receptor R\n",
    "y.activated_by(source=r)    # transcription of Y turned on by activated R.  \n",
    "\n",
    "dinkum.run_and_display(stop=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81a67315-7d29-4321-b973-2e04fc6bfdaf",
   "metadata": {},
   "source": [
    "## An intentional limitation of dinkum: only one regulatory rule is allowed per gene\n",
    "\n",
    "The following model fails; why?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "794a158a-5455-45f9-9351-b56d962fd506",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "initializing: dinkum v0.3.2\n",
      "start=1 stop=10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR: multiple rules containing Y\n",
      "Halting execution.\n"
     ]
    }
   ],
   "source": [
    "dinkum.reset()\n",
    "\n",
    "x = Gene(name='X')\n",
    "y = Gene(name='Y')\n",
    "z = Gene(name='Y')\n",
    "m = Tissue(name='M')\n",
    "\n",
    "z.activated_by(source=y, delay=1)\n",
    "z.activated_by(source=x, delay=2)\n",
    "\n",
    "dinkum.run_and_display(stop=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe1c50c3-a4f4-4c32-84ee-3bc99b34a6cf",
   "metadata": {},
   "source": [
    "The problem here is that we're defining two distinct regulatory interactions for `Z` - it's turned on by X and Y both, in two separate rules. That's not allowed, because dinkum doesn't know how to combine the two interactions. So the rule that dinkum enforces is that there has to be one, and only one, regulatory rule defined for each gene.\n",
    "\n",
    "Here the solution would be to use `z.activated_or(sources=[x,y], delay=1)` or `z.activated_and(sources=[x,y])`, which would establish what kind of interaction `X` and `Y` have in the activation of `Z`.\n",
    "\n",
    "Note that maternal rules (`is_present`) are exempt from this rule."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8afab77b-7350-43b0-9031-155f5d5765e7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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