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Binder

Welcome to the Systems Biology Amsterdam stochastics tutorial

This Github repository contains all materials related to a collection of stochastic/noise practicals taught as part of the systems biology and medicine course at CDAC (Como) 2021 in 2021.

In this tutorial we will use mybinder to run Jupyter notebooks in the cloud. The aims of the tutorial are:

  1. To introduce you to basic programming in Python
  2. Bring your conceptual understanding of stochastics modelling and transcription bursting into practice
  3. Prepare yourself for the lecture 'What if exception rules'

Important notes & tips

  • It is critical that you use a browser other than internet explorer: i.e. Google Chrome, Safari or Firefox.

  • Your work is not saved on the server. So manually export and download the workbooks if you want to keep them as explained in the first notebook.

  • If you are inactive for a while (> 10 min) or randomly due to system errors, the system may quit your session. So when you take a break, make sure you save and export the notebook you are working on first!

  • You can always go back and start the tutorial again or upload your saved files, on any computer at any time in the future.

  • If the group size is large, it is recommended that you work in pairs to reduce server stress.

  • If you run into problems, ask one of the teaching assistants.

Start the tutorial

To start the tutorial, click on the "launch binder" button at the top of this page. You will be redirected to a webpage that will generate a personal jupyter container for you.

After a minute or two the notebook server will be launched. You will see a folder with files.

**Then open the file you want to run either describing:

  1. this tutorial as a whole ['Wff_course_CDAC_2021'],
  2. the section with the tutorial on notebook use ['0_running_code_in_notebook'], or
  3. the section with the tutorial introducing you to the line-by-line programming language Python ['1-introduction_to_python])**.

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Repository meant for course in stochastic modelling of bursting transcription

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