Lecture and Exercise Protein Prediction II for Computational Biologists WiSe 2020/21



Lecture (4 SWS) + Exercise (2 SWS)




Burkhard Rost  (lecture)

Michael Heinzinger (exercise)


Tuesday, 12:30 - 14:00
Thursday, 12:30 - 14:00
Thursday, (exercise), 14:00 - 15:00


Lecture:  virtually

Exercise: virtually

Exam: tba




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First lecture on Tuesday, Nov 10. 12:15am CEST. 
Details in zoom-slides

Our lecture and exercise will be completely virtually.


The link for taking part in online proctoring is sent via mail. If you do not have it by 01.02.2021, 10:00 PM CET, please contact pp1ex@rostlab.org





This lecture continues the 'Protein Prediction I' lecture. The attendance of this lecture however is not a mandatory requirement for 'Protein Prediction II'. Topics will include (but not be limited to):

  • Predicting protein function using sequence: sequence alignments, multiple sequence alignments, motifs, domain assignment, annotation transfer by homology, ab initio predictions.
  • Predicting protein function using structure: structural alignments, structural motifs, annotation transfer via structure similarity.
  • From structure prediction to function prediction: comparative modeling; prediction of: secondary structure, hydrophilicity profiles, solvent accessibility, transmembrane segments, disordered regions, contact maps, functional residues; template free modeling.
  • Machine learning.


  1. Zoom-Slides  Lecture Plan
  2. Lecture 1: Intro Nov 10th - Live Session
  3. Lecture 2: Intro to Protein Function Nov 11th - Video
  4. Lecture 3: Predict Localization  Nov 19th  - Video
  5. Lecture 4: Localization1 Nov 24th - Live on Zoom (12:30pm)
  6. Lecture 5: Localization2 Nov 29th - Live on Zoom (12:30pm) Video
  7. Lecture 6: Localization3 Dec 1st - Video
  8. Lecture 7: Protein Protein Interaction Sites Dec 8th - Live on Zoom (12:30pm)
  9. Lecture 8: Protein Protein Interaction Pairs Dec 10th - Video
  10. Lecture 9: Binding Site & Ligand Interaction Prediction Dec 15th - Video
  11. Lecture 10: Representation Learning Jan 12th - Live on Zoom (start 12:30pm CET)
  12. Lecture 11: Deep Learning Jan 14th - Live on Zoom (start 12:30pm CET)
  13. Lecture 12: SAV effect 1 Jan 19th - Live on Zoom  (start 12:30pm CET) Video1   Video2 Website Issue. Slides temporarily hosted on LRZ Sync+Share
  14. Wrap Up: mock exam - start 12:30pm CET
  15. Wrap Up: Live on Zoom (start 12:30pm CET)



To successfully complete the exercise each group needs to fulfill the following requirements:

  • Give a presentation regarding their project that focuses either on the biological background, current state-of-the-art methods, or the provided data set.
  • Give a final presentation about their approach; e.g. architecture and performance.
  • Actively participate in the exercise. This primarily means attending all students' presentations and participating in the corresponding Q&A sessions.
  • Submit a working solution at the end of the semester. It should be able to make informed predictions based on new data and perform better than a random or very naive solution.

Presentations in general:

  • Attendance is mandatory for all students (not just the groups presenting) whenever there is a presentation by students.
  • For sessions without students' presentations, attendance is not mandatory.

Working in a group:

  • The workload within each group should be evenly split.
  • Not every student has to speak during their group's presentation (e.g. some could work on the presentations, the rest on the programming task).
  • If students in your group refuse to "carry their weight" or you are the only one doing any work, feel free to contact us (better early than late).