Elements of Bioinformatics

Advanced studies
This course gives an introduction to central topics in bioinformatics, including prediction of genes and their function, protein classification and structure analysis as well as biological network analysis.


13.12.2011 09.00 A111
Year Semester Date Period Language In charge
2011 autumn 31.10-08.12. 2-2 English Juho Rousu


Time Room Lecturer Date
Mon 12-14 B222 Juho Rousu 31.10.2011-08.12.2011
Thu 10-12 B222 Juho Rousu 31.10.2011-08.12.2011

Exercise groups

Group: 1
Time Room Instructor Date Observe
Mon 10-12 B119 Esa Pitk√§nen 07.11.2011—09.12.2011

Registration for this course starts on Tuesday 11th of October at 9.00.

Information for international students

 The course in lectured in English.



  • The course has been graded. See results here.
  • Please provide feedback on the course here.


Introdoctory course in bioinformatics (e.g. Algorithms in Bioinformatics, Computational genomics) or equivalent knowledge. 

Main themes

The course explores computational methods (algorithms, probabilistic models, machine learning) in two main themes:

  1. Gene prediction, regulation, RNA life (Lectures on weeks 1-2, groupwork on week 3, exercises on weeks 2-3)
  2. Protein structure, function and networks (Lectures on weeks 1-2, groupwork on week 3, exercises on weeks 2-3)


Completing the course

 The course can be completed in two primary ways:

  1. Lectures, exercises, group work and course exam
  2. Separate exam (first opportunity February 3, 2012)

Grading of the course


The course has three components that contribute towards the grade

  1. Exercises (30%) of the grade. Exercises are completed at home and returned in writing prior to the exercise session to Esa Pitkänen (esa.pitkanen at cs.helsinki.fi)
  2. Group work (20%) of the grade. Two groupwork assignments are completed during the course (3. and 6. week of the course, instead of lectures). The groupwork entails studying a given topic together and preparing a short presentation.
  3. Course exam (50%) of the grade. Course exam will be on Tuesday December 13, at 9.00am. Examined contents are the lectures and exercises.


Literature and material

 The course is not based on a particular course book. The material comes from variety of books and scientific articles.

The lecture slides will appear here after each lecture.

  • Lecture 1: slides
  • Lecture 2: slides. Course folder in room C127 contains additional reading material on HMMs. Please take a copy and return to the folder.
  • Lecture 3: slides
  • Lecture 4: slides
  • Lecture 5: slides
  • Lecture 6: slides
  • Lecture 7: slides
  • Lecture 8: slides

Exercises and their solutions will appear here:

 Groups and topics for groupwork will appear here:

Inormation about the course Exam

Course exam will be held 13.12 at 9.00am, lecture hall A111.

The examined contents

  • Lectures 1-8
  • Exercises 1-5

The group works 1-2 will not be part of the exam.

The exam will have

  • 5 questions, each worth 10 points in total
  • A mix of essay style and technical questions.

You may use a scientific calculator in the exam.


Additional reading:

R. Durbin, S. Eddy, A. Krogh, G. Mitchison: Biological sequence analysis: Probabilistic models of proteins and nucleic acids. Cambridge University Press, 2001

Asa Ben-Hur, Cheng Soon Ong, Sören Sonnenburg, Bernhard Schölkopf, Gunnar Rätsch: Support Vector Machines and Kernels for Computational Biology. PloS Computational Biology 4(10): e1000173.

Jean-Philippe Vert: Reconstruction of biological networks by supervised machine learning approaches. Technical report hal-00283945, 2008