- The first lecture will take place on February 8.
- Lectures: Mondays 12:15 - 14:00 in Zoom ( (log into courses to see link) )
- Practice sessions/Consultations: Thursdays 10:15 - 11:45 in Zoom ( (log into courses to see link) )
- Project selection: TBD
- BIIT (Bioinformatics, Algorithmics, and Data Mining group) group website : http://biit.cs.ut.ee/
- Assingment submissions: Assignments
- Course materials: https://github.com/kauralasoo/MTAT.03.239_Bioinformatics
- Lecturers: Kaur Alasoo (kaur.alasoo [at] ut.ee), Erik Abner, Priit Adler
- Projects: link
- Lecutre recordings: link
- Lecture slides: link
- Slack: sign up
Although the course has no official pre-requisites, basic programming and data analysis skills are required to successfully complete the homework and project assignments.
- 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:
- Assignments (50 points): there will be ~10 assignments, each worth ~5 points;
- Group project and presentation at the poster session (50 points);
- Additional points can be earned from bonus tasks within assignments;
In order to pass the course, the student must get at least 50% from assignments (threshold 25 points), at least 50% from the project (threshold 25 points).