Modelling and Analysis in Bioinformatics

Vuosi Lukukausi Päivämäärä Periodi Kieli Vastuuhenkilö
2016 syksy 06.09-20.10. 1-1 Englanti Antti Honkela


Aika Huone Luennoija Päivämäärä
Ti 12-14 B222 Antti Honkela 06.09.2016-20.10.2016
To 10-12 B222 Antti Honkela 06.09.2016-20.10.2016


Group: 1
Aika Huone Ohjaaja Päivämäärä Huomioitavaa
To 12-14 B221 05.09.2016—21.10.2016


The course explores computational models for biological networks, including e.g. network motifs and gene regulation, and introduces probabilistic analysis of sequence-level problems in fragment assembly, pattern matching, and motif discovery. The course is lectured by Juha Kärkkäinen, Leena Salmela and Antti Honkela.

Basic information

Credit points (ECTS): 5
Prerequisites: basic programming skills (Python)

Kurssin suorittaminen

The course consists of lectures, study groups and programming exercises. Attendance in the study groups and visiting lectures is mandatory. In case you cannot attend a study group or a visiting lecture, contact the lecturers for an alternative assignment. Python language is used for the programming exercises.



You can work on the exercises with a pair or alone. Submit your solutions as an ipynb file using Moodle.

The exercises consists of small programming projects in Python. We will use Python version 3 for the exercises. Exercises are given as Jupyter Notebook documents that you should complete to include your solutions. Moodle has instructions on how to use the Jupyter Notebook environment on CS department Linux workstations and you can also install it on your own computer. To get started with the exercises:

  • Create a directory for your notebooks
  • Copy the exercise file into that directory
  • Open a terminal and move to the directory
  • Run 'jupyter notebook'

This will start the Jupyter Notebook system and open a web browser for you in which you can start working on the exercises. When you are done, close the web browser and issue Ctr-C twice in the terminal window to shutdown the environment.


To pass the course:

  • Attend study groups and visiting lectures
  • Submit the programming exercises and get at least 6 points in each of the three exercise sets (probabilistic analysis of sequence-levels problems, network models, network inference)

The course will be graded in the scale 1-5. Grading is based on the submitted programming exercises. In total 60 points will be available. To pass the course you must get  at least 30 points and a grade of 5 will require 50 points. If the exercises prove to be very difficult, these limits may be lowered.

The course does not include an exam and it is not possible to pass the course with a separate exam.