Laboratory of Computer and Information Science / Neural Networks Research Centre CIS Lab Helsinki University of Technology

T-61.5050 High-throughput bioinformatics V P, 5/7 cr

(Title in Finnish: T-61.5050 Suurkapasiteettimittausten bioinformatiikka V L)

Lecturers D.Sc.(Tech) Janne Nikkilä, Laboratory of Computer and Information Science,
Doc. Petri Auvinen, Institute of Biotechnology,
D.Sc. Alvis Brazma, European Bioinformatics Institute, Microarray group
Assistant M.Sc. Merja Oja, Laboratory of Computer and Information Science
Semester Spring 2007 (during periods III and IV)
Lectures On Thursdays at 14-16 in room T3 in the computer science building,
Konemiehentie 2, Otaniemi, Espoo. The first lecture on 18.1.2005.
Exercises On Thursdays at 16-18 in room A328.
Language English


This year the main topic is data analysis for gene expression.

Microarray technology has made it possible to monitor large-scale gene expression (the level of activation of genes) and has become incredibly popular in genomics research. This high-throughput technique can provide information for thousands of genes in parallel and is producing huge amount of valuable data. Data sets can easily have tens, hundreds of thousands or even millions of data points. This necessitates use of sophisticated data-analysis tools for processing and data mining of this type of genomic data, to understand the underlying genetic networks and to answer the complex biological and medical questions involved.

This course is designed to introduce computational and statistical concepts and tools necessary to analyse microarray-based gene expression data, a skill that is in high demand by biotechnology, bioinformatics and pharmaceutical companies. The skills learned in this course will also be applicable to other problems involving large data sets, such as proteomics, and more generally in data mining.

Prerequisites for attending

This course is intended mainly for advanced undergraduate (Master's level) and doctoral students and of computer science, statistics, and applied mathematics, but students from other fields are welcome as well. In particular mathematically oriented biology, bioinformatics, and medical students should benefit from the course.

Basic knowledge of probability, statistics, vector algebra, and calculus is assumed (the basic mathematics courses in HUT). A "Basic course in bioinformatics", such as S-114.2510 Computational Systems Biology or equivalent background is assumed as well.

Course format

The course contains the following parts: lectures, exercise sessions, homework assignments, an intensive course (Tue 10-12, Thu 14-16 and Fri 14-16, between 13.2.-1.3.) and an exam.

Course material

The lectures will be based on the book: Sorin Draghici, Data analysis tools for DNA microarrays
(Chapman & Hall/CRC, 2003)

Janne Nikkilä, Petri Auvinen, Alvis Brazma, Merja Oja

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