The following listing and comments refer to the degree requirement structure of MBI at University of Helsinki. MBI students at Aalto University should consult their student councellor on mapping the courses to the corresponding modules. Please see also Aalto-specific pages on MBI.

Bioinformatics courses / Autumn 2010 (preliminary)

This list includes the major courses. Note that some of them can also be included as minor subject studies in Computer science, Statistics, Biology.

period I

582670 Algorithms for Bioinformatics (4 cr), period I
Professor Veli Mäkinen 06.09.-13.10. Mon 12-14, Wed 10-12 B222
Course introduces basic algorithmic concepts through motivation by selected computational molecular biology problems.
Placement: 1st year

57748 Molecules for bioinformatics (4-6 cr), period I
University Lecturer Sirkka-Liisa Varvio. 08.09.-23.09. Tue 14-17, Wed 16-18, Thu 14-17 D122, in addition 2h computer class (TBA). Molecules as statistical and computational challenges, genomic compartments and polymorphisms and principles of their statistical analyses, basics of genetics, structure and evolution of the domains of life. Associated course is
57780 Genetic analysis (2 cr), 08.09-27.10, Wed 12-16, B120. Placement: 1st year

57046 Markovian modelling and Bayesian learning (5 cr), period I
Professor Jukka Corander. 28.09.-14.10, Tue 14-17, Wed 16-18, Thu 14-17, D122.
Various types of Markovian probability models and assumptions. A central aim to gain understanding in how models can be built for various phenomena by using ordinary and hidden Markov assumptions. Introduction to Bayesian learning and its uses. Prerequisites are principles of probability. Those lacking such can take an associated course
57781 (2 cr, Introduction to probability with R, 09.09-23.09, Thu 10-14, Fri 4-16,B120.
Placement: 1st year

T-61.5120 Computational genomics (4 cr), period I
Teaching Researcher Fabian Hoti. Mon 12-14, Tue, 10-12, Exercises Tue 8-10,
Algorithms and models for biological sequences and genomics.
Placement: 1st year

T-61.3050 Machine learning: Basic principles (5 cr), period I
PhD Tapio Raiko. Mon 10-12, Fri 10-12, Exercises Wed 12-14, Fri 12-14
Placement: 1st year

period II

582673 Computational Genotype Analysis (4 cr), period II
Academy Research Fellow Mikko Koivisto 01.11.-08.12. Mon, Wed 10-12 B222
We will study statistical and algorithmic methods for the analysis of genetic variation in SNP (single nucleotide polymorphism) genotype data.
Prerequisites: basics of genetics and statistics.
Placement: 1st or 2nd year

582313 Elements of Bioinformatics (4 cr), period II
Professor Veli Mäkinen 01.11.-09.12. Mon 12-14, Thu 10-12 B222
This course gives an introduction to the central topics in bioinformatics, and gives a foundation for further courses in the Master's Degree Programme in Bioinformatics (MBI).  Prerequisites: I period MBI courses 582670, 57046, and 57748, or equivalent knowledge.
Placement: 1st year

582631 Introduction to Machine Learning (4 cr), period II
Academy Research Fellow Patrik Hoyer 02.11.-10.12. Tue, Fri 10-12 D122
Basic concepts and methods of machine learning, in theory and in practice. Supervised learning (classification, regression) and unsupervised learning (clustering). The course serves as preparation for various courses on data analysis, machine learning and bioinformatics.

T-61.5110 Modeling biological networks (5-7 cr), period II
Professor Harri Lähdesmäki. Tue 14-16, Fri 10-12, Exercises Mon 8-10, Fri 12-14
Placement: 1st or 2nd year

57749 Evolution of disease genes (4-6cr), period II
University Lecturer Sirkka-Liisa Varvio. Wed 03.11 12-16 C129, Thu 04.11 14-18 B120,  see course webpage for further information. 

Placement 1st or 2nd year

Seminars

T-61.6080 Special course in bioinformatics II (3-7 cr), periods I-II
Professor Erik Aurell. Thu 12-14
Placement: 2nd year

58309106 Seminar: Machine Learning in Bioinformatics (3 cr), periods I-II
Professor Juho Rousu 06.09.-11.10. Mon 14-16 C220, 01.11.-29.11. Mon 14-16 C220
Placement: 2nd year

58307312 Master's thesis seminar MBI  (3 cr), periods I-IV
University Lecturer Esa Pitkänen 06.09.-11.10. Mon 16-17 B222, 01.11.-29.11. Mon 16-17 B222
While working on the Master's thesis, the student is expected to participate in the Master's thesis seminar on a regular basis and give two presentations, one on the research plan and the other on the (nearly) completed thesis in the seminar. The Master's thesis seminar operates throughout the year.
Placement: 1st and 2nd year

Courses in biosciences / Autumn 2010

399673 Cellular imaging (1 cr), period I
Jussi Kenkkilä, Wed 06.10, 9-15, Fri 08.10, 9-15, Wed 13.10, 13.30-17.30, Biomedicum.
The world within cells through of various sortes of microscopic techniques. Note: this course corresponds to one module of course Measurement techniques with respect to degree requirements.

Links to other biology courses:

• Department of Biological and Environmental Sciences (Viikki)
• Faculty of Agriculture and Forestry (Viikki)
• Faculty of Pharmacy (Viikki)
• Curriculum 2010-2011, Master's Degree Programme in Biotechnology
• Curriculum 2010-2011, Master's Degree Programme in Plant Production Science

Courses in computer science, mathematics and statistics / Autumn 2010 (preliminary)

Some of the listed courses can also be included as major subject studies in bioinformatics (if in accordance with an approved personal study plan). Please see this page for links to more complete course lists at individual departments.

period I

57739 Statistical methods in medicine and epidemiology (6-10 cr), periods I-II
Adjunct professor Kari Auranen. I period Tue and Thu 17-19, II period Tue and Thu 18-20, D122
Placement: 1st or 2nd year

57394 Adaptive dynamics (10 cr), periods I-II
University lecturer Stephan Geriz. Tue 14-16, B321, Thu 14-16, B322.

57043 Linear algebra and matrices I (5 cr), period I
University lecturer Juliette Kennedy, Mon 16-18 C123, Wed 10-12, B120.

57421 Levy processes (5 cr), periods I and II
Juha Vuolle-Apiala, Fri 10-12, B321.
Stochastic processes with independent, stationary increments. They are translation invariant and have the strong Markov property. The most well-known examples are Brown motion and Poisson process.

582630 Design and Analysis of Algorithms (4 cr), period I
PhD Valentin Polishchuk 07.09.-15.10. Tue 12-14 C222, Fri 12-14 B222
General design principles of algorithms. Examples of central problems and typical solutions. Average case analysis. Amortised complexity. Recurrences. NP-completeness. Prerequisites: the course Data Structures or equivalent. Course book: T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein: Introduction to Algorithms, 3rd ed., MIT Press, 2009.
 

T-61.5060 Algorithmic methods of data mining (5 cr), period II

PhD Panagiotis Papapetrou. Mon, Fri 10-12, Exercises Thu 16-18
Placement: 1st or 2nd year

T-61.5080 Signal processing in neuroinformatics (5 cr), periods I-II
PhD Ricardo Vigario. Thu 14-16

T-61.3040 Statistical signal modelling (5 cr), periods I-II
PhD Jaakko Peltonen. Tue 14-16, Exercises Thu 10-12

period II

57703 Data-analysis with R (5 cr), period II
Jouni Junnila. Mon 16-18, Thu 8-10, CK112.
Placement: 1st or 2nd year

57047 Linear algebra and matrices II (5 cr), period II
University lecturer Juliette Kennedy, Mon 16-18 C123, Wed 10-12, B120.

T-61.5130 Machine learning and neural networks (5 cr), period II
Professor Juha Karhunen. Mon 12-14, Tue 14-16,  Exercises Thu 10-12, Fri 12-14
(exception week 44 Tue lecture at 12-14)

58093 String Processing Algorithms (4 cr), period II
University Researcher Juha Kärkkäinen 02.11.-09.12. Tue, Thu 12-14 B222
Basic algorithms and data structures for string processing: exact and approximate string matching, string sorting, dictionary data structures, text
indexing.

Language courses at University of Helsinki (preliminary)