Institute of Computer Science
  1. Courses
  2. 2017/18 spring
  3. Bioinformatics (MTAT.03.239)
ET
Log in

Bioinformatics 2017/18 spring

  • Main
  • Schedule
  • Homework
  • Additional reading
  • Introductory biology
  • Projects

Bioinformatics (MTAT.03.239)

Course info

  • 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/

Contacts

  • 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)

Learning objectives:

  • 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).

  • Institute of Computer Science
  • Faculty of Science and Technology
  • University of Tartu
In case of technical problems or questions write to:

Contact the course organizers with the organizational and course content questions.
The proprietary copyrights of educational materials belong to the University of Tartu. The use of educational materials is permitted for the purposes and under the conditions provided for in the copyright law for the free use of a work. When using educational materials, the user is obligated to give credit to the author of the educational materials.
The use of educational materials for other purposes is allowed only with the prior written consent of the University of Tartu.
Terms of use for the Courses environment