Bioinformatics Centre > Education > Master's degree in Bioinformatics > Content of Programme

There are three types of courses in the programme:

• Core courses are mandatory bioinformatic courses that cover the fundamentals of bioinformatics and they take up half the time of the first year of study. They total 30 ECTS points.
• Special Modules: These are either specialized courses in bioinformatics or projects (7,5 or 15 ECTS) that can be made in groups or individually. Often a project is made as a prelude to the Master's thesis. A minimum of 22.5 ECTS points is required from special modules.
• Supplementary courses (in Danish: Redskabskurser) are courses in topics necessary to understand and work with bioinformatics, such as statistics. Students with a Bachelor's degree in a biological discipline would typically take courses in programming and someone from computer science would take a course in e.g. molecular biology. Supplementary courses are allowed up to a miximum of 37.5 ECTS points.

Thus only one third of the program is mandatory, which leaves thestudent with great possibilities to specialize in a certain direction. 

Core Courses

The goal of the core courses is to give the students a firm background from which they can evolve in any of the bioinformatics subfields.  Each core course is taught by a group leader who is an expert in the field. Meet the teachers here .

Biological Sequence Analysis: In this course you learn the fundamentals of biological sequence analysis, which forms the basis fora large part of bioinformatics. The topics include pairwise alignment, multiple alignment, substitution matrices, database searching, Blast, hidden Markov models and sequence profiles. In the lectures the emphasis is on the theory and in the exercises you will learn how to solve pratical problems using available programs. The course is taught by  Anders Krogh  and the textbook is Biological Sequence Analysis co-authored by Anders.

Structural Bioinformatics: Bioinformatics is mostly associated with the analysis of biologicalsequences and data mining genomes. But bioinformatics is much more thanthat! All biological molecules are three-dimensional structures, andinformation on this structure is of high importance for applicationssuch as drug design and biotechnology. In this course, you will get athorough introduction to structural bioinformatics, that is, thescience of understanding the link between molecular structure and function through computational procedures. Topics discussed in thecourse include protein structure analysis (including experimental methods), protein and RNA structure prediction and prediction of protein function from structure. Invited speakers from industry andacademia discuss topics such as structure based drug design and protein engineering. You will learn how to develop your own custom-made algorithms and applications using Python and Biopython.Many of the algorithms that will be discussed are also used inartificial intelligence, gaming and robotics. The course is taught by Thomas Hamelryck .

Bioinformatics of high-throughput analysis A wealth of experimental methods can now be applied to study wholegenomes at once: this includes tiling arrays, Chip-Chip and tag-based sequencing. These types of data sets are too large and complex to analyze by hand or by using spreadsheet programs. The primary aim oft his course is to introduce the students to bioinformatics methods tohandle, visualize, analyze and interpret high-throughput experimental data, such as gene expression data, proteomics data, CAGE, SAGE and sequencing data. A large part of the course consist of hands-on exercises in class, using (and learning) the R environment - a very powerful statistics platform which is free to download.  This course is taught by Albin Sandelin

Special Modules

These courses cover more specialized bioinformatics topics.

Bioinformatics Project You can choose a topic for a project together with a supervisor at the bioinformatics centre or elsewhere.These projects are typically related to some research project. For instance, you can theoretically describe a new method for solving aproject, implement it and test it on real data. You register for the project as you do for any other course. You have to hand it in at a specified date at the end of the block and you have to "defend it" at an oral exam.

Individual Project The individual project is similar to ablock project, but it can be both 7.5 and 15 ECTS points and you are only allowed to do individual projects when you have passed the mandatory courses. It is also more free with respect to deadline, onwhich you agree with the supervisor at the beginning of the project. There is no exam - the grade is based entirely on the written project.This type of project is really well suited as a prelude to the master'sproject.

Courses elsewhereCourses taken in other departments or institutions, which have to be pre-approved by the study board.

Supplementary Courses

Bioinformaticians have strong skills in biology, statistics andbiology. A couple of crash courses have been designed to bring students without prior knowledge in these fields up to speed:

Linux and Python Programming: This course teaches students touse a Linux/Unix operating system, and to solve programming tasks inPython. It is meant as a general introduction to programming andrequires no previous programming experience. The course will include topics as: a) Unix/Linux: basic navigation, pipes, configuring the shell, standardunix tools, networking, and process control. b) Programming:programming basics, datatypes, object oriented programming, regularexpressions, solving numerical tasks, recursive datatypes/functions,computational complexity, and some basic algorithms for searching andsorting.

Statistics for bioinformaticians: The aim is to make the student capable of using statistical methods for the analysis of data related in particular to bioinformatic, molecularand evolutionary biology problems. Moreover, problems are attempted solved with the aid of a computer rather than mathematically.Content: Probability measures on discrete and continuous sample spaces.Certain fundamental models like the binomial, multinomial and thenormal distribution. BLAST and the Gumbel distribution. Descriptivestatistical methods, e.g. empirical measures, tables, average andstandard deviation, histograms, QQ-plots and boxplots. Simulations and the statistics program R. Parameterised models and maximum likelihoodestimation. Evolution models like Jukes-Cantor and Kimura. Confidenceset and bootstrapping. Prediction and classification.

Introduction to Molecular Biology and Genetics: The course is intended for bioinformatics students without any priorknowledge on biological issues such as macromolecular structure, gene regulation, DNA replication, transcription and translation. The aim ofthe course is to give such students the necessary introduction to thesesubjects at a level needed to appreciate and comprehend the teaching inthe core courses of bioinformatics. The students will become familiar with membrane structures, proteins and intracellular compartments andalso with subjects like genome evolution and experimental methods.Contens: DNA repair, replication, transcription and translation. Regulation of gene expression, cell cycle and cell communication. Proteins, intracellular transport, membrane transport and membranestructures.

Master thesis

As the conclusion of the programme all students have to write a master thesis (30 ECTS).

A sample of previous master thesis reports is here.