Readme Upate & Pre-print updates

- updating readme with pre-print info - adding preprint link to jnb example
OpenFreeEnergy · Sep 17, 2024 · 199903d · 199903d
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diff --git a/README.md b/README.md
@@ -33,26 +33,28 @@ Last we want to bring to your attention our Network visualization tools and the
 
 Try our interactive demo: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/OpenFreeEnergy/konnektor/blob/main/examples/konnektor_example.ipynb#scrollTo=GU32PaMkzD7x)
 
+For more information checkout our pre-print: [Konnektor: A framework for using graph theory to plan networks for free energy calculations](https://chemrxiv.org/engage/chemrxiv/article-details/66d9b574cec5d6c1423643e4)
+
 
 ## Content
 ### Implemented Network Layouts
 Several Network layout generating algorithms are implemented in Konnektor, with different advantages and disadvantages.
 From an algorithmic perspective most of the algorithms are actually a reduction method of the Maximal Network.
 To speed-up the Maximal Network Algorithm we implemented an parallelization scheme to it. Below you can find some of our layouts:
 
-![image](.img/network_layouts.png)
+![image](docs/_static/img/network_layouts.png)
 
 ### Tools for handling Networks
 Konnektor implements tools, that allow for example to merge (if a node is shared in the networks) or concatenate (if no node is shared) networks,
 append single molecules (nodes) to a network or delete transformations/molecules from a network.
 
-![image](https://github.com/OpenFreeEnergy/konnektor/assets/12428005/5fbb253c-f0d3-41bf-bd92-f520b1363b6d)
+![image](docs/_static/img/network_operations_small.png)
 
 ### Enable More Complex Higher Order Networks
 Another goal of Konnektor is to go beyond the standard network layout algorihtms and allow easy implementation of more complex network algorithms.
 This is achieved by combining the Tools and Network Generator Algorithms, to build up to more advanced workflows.
 
-![image](https://github.com/OpenFreeEnergy/konnektor/assets/12428005/c4ee0b63-7580-4825-b0cb-dc076e4cb9f4)
+![image](docs/_static/img/advanced_networking.png)
 
 ## Code Example
 

diff --git a/docs/_static/img/advanced_networking.png b/docs/_static/img/advanced_networking.png
diff --git a/.img/network_layouts.png → docs/_static/img/network_layouts.png b/.img/network_layouts.png → docs/_static/img/network_layouts.png
diff --git a/docs/_static/img/network_operations_small.png b/docs/_static/img/network_operations_small.png
diff --git a/examples/konnektor_example.ipynb b/examples/konnektor_example.ipynb
@@ -42,7 +42,8 @@
    ],
    "metadata": {
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-   }
+   },
+   "execution_count": null
   },
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    "cell_type": "markdown",
@@ -986,7 +987,7 @@
     "\n",
     "The consequence of a edge failure can be deduced from the *graph robustness*, for the  __Star Network__ any edge failure leads to the same amount of `Component`s lost in the final ranking. The __Starry Sky Network__ seems to recover from an $1\\%$ edge loss to about ~ 10% of the cases, which does not make it a very robust approach either. Only the __Redundant MST Network__ is able to withstand the $1\\%$ edge failure without losing any `Component` in the final ranking. This robustness is an effect from the high *average node connectivity* of the __Redundant MST Network__. An additional interesting aspect of the __Redundant MST Network__ is the large generated number of cycles, which can be used for advanced analysis of the final free energy calculation results.\n",
     "\n",
-    "A larger comparison of Networks can be found in our pre-print: ![]()\n"
+    "A larger comparison of Networks can be found in our pre-print: [Konnektor: A framework for using graph theory to plan networks for free energy calculations](https://chemrxiv.org/engage/chemrxiv/article-details/66d9b574cec5d6c1423643e4)\n"
    ]
   },
   {