diff --git a/analysis/Tutorial/mibitof_tnbc_tutorial.ipynb b/analysis/Tutorial/mibitof_tnbc_tutorial.ipynb
index f36d428..9754f67 100644
--- a/analysis/Tutorial/mibitof_tnbc_tutorial.ipynb
+++ b/analysis/Tutorial/mibitof_tnbc_tutorial.ipynb
@@ -38,7 +38,9 @@
     "FANMOD_path = \"C:\\\\Users\\\\User\\\\source\\\\repos\\\\fanmod-cmd\\\\out\\\\build\\\\x64-release\" #this should be updated\n",
     "FANMOD_exe = \"LocalFANMOD.exe\"\n",
     "output_dir = './../../fanmod_output'\n",
-    "cache_dir = './../../parse_cache'"
+    "cache_dir = './../../parse_cache'\n",
+    "\n",
+    "cism_project_root_path = 'C:\\\\Users\\\\milsh\\\\PycharmProjects\\\\CISM'"
    ]
   },
   {
@@ -366,6 +368,17 @@
    "cell_type": "code",
    "execution_count": 28,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Changing directories so we can import CISM objects\n",
+    "import os\n",
+    "os.chdir(cism_project_root_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -455,6 +468,17 @@
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Changing directories back to the tutorial\n",
+    "import os\n",
+    "os.chdir(cism_project_root_path + '\\\\analysis\\\\Tutorial')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -626,6 +650,19 @@
    "cell_type": "code",
    "execution_count": 15,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Changing directories so we can import CISM objects\n",
+    "import os\n",
+    "os.chdir(cism_project_root_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "data": {
@@ -692,6 +729,17 @@
    "execution_count": 16,
    "metadata": {},
    "outputs": [],
+   "source": [
+    "# Changing directories back to the tutorial\n",
+    "import os\n",
+    "os.chdir(cism_project_root_path + '\\\\analysis\\\\Tutorial')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "from cism.cism import TissueStateDiscriminativeMotifs\n",
     "from cism.cism import DiscriminativeFeatureKey\n",
@@ -842,6 +890,19 @@
    "cell_type": "code",
    "execution_count": 20,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Changing directories so we can import CISM objects\n",
+    "import os\n",
+    "os.chdir(cism_project_root_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -997,7 +1058,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "79f06f0e3c56465d9b565f27aa760f88",
+       "model_id": "9f247ecc9104465c8f4e078f3fa6a59d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1011,7 +1072,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b1e9e84daefb4d8bbac3bb568ef140a7",
+       "model_id": "fa66119f47b5469999aad7a5e2eccc47",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1026,14 +1087,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "classes: ['Short-term survival', 'Long-term survival'] th:0.5 score: 0.7619047619047619\n",
+      "classes: ['Short-term survival', 'Long-term survival'] th:0.5 score: 0.7904761904761904\n",
       "task: Short-term survival - Long-term survival\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e5027c40b5a34e979c8d7804c1089823",
+       "model_id": "60f5ce59c5c446a79139333619e59842",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1047,7 +1108,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "77b56d9012c64959bbfed9f0120d3fda",
+       "model_id": "ee25cd9609364998b905531823ff7d43",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1069,7 +1130,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7aa321fa9891467db7e8aca07fa9f1c5",
+       "model_id": "f0cc6a4d2f4e4c998d1147266deb88f5",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1083,7 +1144,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "42616a8bab164d57aa4fb4342d8bfb4e",
+       "model_id": "1154390e7243447492f7f80d84d9f259",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1105,7 +1166,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "16a0144de57e4e23be03bebfaeca6eba",
+       "model_id": "e80cc956af2a4322bae07f8baf20add2",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1119,7 +1180,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "06696fcdb7c84df29e98c5b98843397a",
+       "model_id": "ae706ef6a8434318935b6952c3d66b8d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1134,14 +1195,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "classes: ['Short-term survival', 'Long-term survival'] th:0.75 score: 0.7380952380952381\n",
+      "classes: ['Short-term survival', 'Long-term survival'] th:0.75 score: 0.7333333333333334\n",
       "task: Short-term survival - Long-term survival\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5276197cf2444f15977aac74c9728c7f",
+       "model_id": "8a31013922644920b08533175f4d6724",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1155,7 +1216,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "17f464bce407409eb4811da28d6d5814",
+       "model_id": "b93dfe4866e24d28adc01772a883cf6d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1238,13 +1299,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "093dddf3f3c744b49bf60f72c50ee9e4",
+       "model_id": "0607e34541a44cbdb1e2578b42d882eb",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1277,14 +1338,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "we have 33 discriminative motifs\n"
+      "we have 31 discriminative motifs\n"
      ]
     }
    ],
@@ -1301,7 +1362,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
@@ -2023,13 +2084,6 @@
     "    target_motif = helpers.string_base64_pickle(target_motif)\n",
     "    draw.draw_motif(target_motif, cells_type=cells_type)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {