- The first meeting will take place on February 15.
- Lectures: Thursday 14:15 - 16:00, J. Liivi 2 - 111
- Practice sessions: Thursday 16:15 - 18:00, J. Liivi 2 - 111
- Consultations: Monday 12:00-13:00 (J. Liivi 2 - 225) and Wednesday 16:00-17:00 (J. Liivi 2-611)
- Project selection: link
- BIIT (Bioinformatics, Algorithmics, and Data Mining group) group website : http://biit.cs.ut.ee/
- Course forum: Piazza
- Homework submissions and grades: Gradeoscope (Entry Code: 93YNJG)
- Course materials: https://github.com/kauralasoo/MTAT.03.239_Bioinformatics
- Lecturer: Kaur Alasoo (kaur.alasoo [at] ut.ee)
- You will learn how to transfer the theoretical skills that you have learned in Data Mining, Neural Networks and Algorithmics courses to practical data analysis problems, with a particular focus on biology.
- You will know how to assess the quality of data via exploratory analysis (clustering, PCA) and know how to detect and when to remove outlier samples.
- You will understand the basic concepts of information flow in biological systems (genetic variant -> TF binding -> gene expression -> protein expression -> cellular phenotypes/imaging -> organismal phenotypes ) and what are the main biological and computational approaches to analyse it.
Grading and requirements:
The grade is calculated from the total number of points (max 100). The points can be earned as follows:
- Homeworks (50 points): there will be 10 homeworks, each worth 5 points;
- Group project and presentation at the poster session (20 points);
- Written exam (30 points);
- Additional points can be earned from bonus tasks within homeworks;
- Attending at least 8 out of 11 practice sessions is compulsory: after missing 3 practice sessions each additional missed practice session results in losing 5 points.
In order to pass the course the student must get at least 50% from homeworks (threshold 25 points), at least 50% from the project (threshold 10 points) and at least 50% from the exam (threshold 15 points).