Skip to content

Latest commit

 

History

History
86 lines (63 loc) · 4.18 KB

README.md

File metadata and controls

86 lines (63 loc) · 4.18 KB

CADDSeminar_2023

Teachers

  • Michael Backenköhler
  • Paula Kramer
  • Floriane Odje
  • Andrea Volkamer

Link to CS seminar description.

General guidelines for each assignment

  1. Initial session: Research your topic and write the theory part of your notebook. You will be provided with some references but you are also expected to do some complementary reading if needed. On May 9th you will have to present it to the class (briefly).
  2. Work sessions (3 lessons): write your talktorial notebook. The final result should be comparable with the notebooks from TeachOpenCADD. Please push your progress to this repo at Monday 1 pm the latest, so we have time to check your talktorials until Tuesday mornings.
  3. Presentation sessions (2 lessons): Present your notebook to the class.

Course dates

The seminar will be on Tuesdays, starting at 10:15 am.

Date Course content
25.04. Introduction and topic assignment
09.05 Short presentations + Q&A
23.05. Working on talktorials (I) + Q&A
06.06 Working on talktorials (II) + Q&A
20.06 Working on talktorials (III) + Q&A
27.06 Student presentations (I)
04.07 Student presentations (II)
11.07 Student presentations (III)

Topic assignments

Topic Name
Diffusion-based docking model Hamza Ibrahim
Scaffold-based data split Vahid Atabaigielmi
Protein Folding Mhd Jawad Al Rahwanji
Drug combination prediction with SVM Vanessa Siegel

Before you start

Make sure you have conda installed in your OS, see Miniconda for Python 3.10

How to start working

Clone repo

  1. Clone the volkamerlab/CADDSeminar_2023 repository
    • using git clone [email protected]:volkamerlab/CADDSeminar_2023.git
    • or... git pull on master (to get all updates!
  2. Change into seminar folder: cd CADDSeminar_2023

Create enviornment

  1. Create enviornment: conda env create --file environment.yaml
  2. Activate the environment with conda activate <my_env>
  3. You can find a conda cheat sheet here.

Create your own branch

  1. Create a new branch called T[mynb]-[your_initials]-[topic] (e.g. T01-AV_proteinfolding) using git checkout -b T[mynb]-[your_initials]-[topic]
  2. Copy and paste the folder 0[nr]_topicname/ in notebooks/ and rename it with your own topic number and topic name. This can be done using cp -r notebooks/0[nr]_topicname notebooks/[mynb]_[mytopicname] .
  3. Rename the talktorial_template.ipynb notebook in your topic folder as T[mynb]_[mytopicname].ipynb. This can be done using mv talktorial_template.ipynb T[mynb]_[mytopicname].ipynb.

Start your work

  1. Run jupyter notebook and open your notebook T[mynb]_[mytopicname].ipynb through the web-app
  2. Fill the template with the theory and start working.

Version control

  1. Save, stage and upload your changes using
    • git add <my_file>,
    • git commit -m 'message associated to commit.'
    • and git push origin T[mynb]-[your_initals].
    • Be aware of the new files you add!
  2. You will now be able to create your pull request on GitHub on the volkamerlab/CADDSeminar_2023 repo. Rename the title of your PR as T[mynb]-[your_initials].

Useful links & Cheatsheets