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Jupyter Notebooks for learning the PyRosetta platform for biomolecular structure prediction and design

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PyRosetta Workshops

Getting Started

Students

Step 1: Sign in to Google Drive.

Step 2: Make a new folder called “PyRosetta” in your top level directory on Google Drive. PyRosetta folder

Step 3: Get your PyRosetta license.

Step 4: Download the Linux PyRosetta package that is called "Python-3.6.MinSizeRel". Linux Download

Step 5: Upload the Linux PyRosetta package (.tar file) to the PyRosetta folder in your Google Drive.

Step 6: Go to https://github.com/RosettaCommons/PyRosetta.notebooks and download the ZIP folder. ZIP

Step 7: Upload either (or both) the student-notebooks folder and the notebooks folder to the top-level directory of your Google Drive. nb Google Drive

Step 8: From the notebooks or student-notebooks folder, open up “01.01-PyRosetta-Google-Drive-Setup.ipynb” in Google Colab by right-clicking, going under “Open With…” and clicking Google Colaboratory.

Step 9: Follow steps to install PyRosetta. You will see a bar and a lot of output, and it should take 10-15 minutes. Note: You only need to do this once since this installation will be associated with your Google Drive account. install

Step 10: Open up “01.02-PyRosetta-Google-Drive-Usage-Example.ipynb” in Colab to make sure that PyRosetta was installed properly. You are now ready to move on to the other notebooks!

Instructors

Step 1: Please install extensions nbgrader and nbpages.

Step 2: Make any changes to the workshops in the "notebooks" folder. (You can follow the directions for students and edit them in Google Colab or on your own computer using a Jupyter Notebooks browser.)

Step 3: When you are done making changes, run make-student-nb.bash to automatically generate the student notebooks in a separate folder, the table of contents you see below, and the keyword index. The student notebooks are copies of the instructor's version that have omitted solutions.

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Jupyter Notebooks for learning the PyRosetta platform for biomolecular structure prediction and design

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