Lecture and Exercise Protein Prediction II for Computational Biologists WiSe 2021/22


 

Type:

Lecture (4 SWS) + Exercise (2 SWS)

Ects:

8.0

Lecturer

Burkhard Rost  (lecture)

tba (exercise)

Rotation:

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

Place:

Lecture: Virtual (Potential for in-person Q&A)

Exercise: Virtual

Exam: tba

Language:

English

Announcements:

The latest news are always on top!

First lecture on Thursday in the second lecture week!

Exam

 

Communication

For this course, we will use Moodle. You will be automatically registered.

 


Content

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.

Slides

Exercise

Slides

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).