ll courses funded by this research school will make all of its material freely available online to everyone in the world using the Creative commons 3.0 license. Lectures will be recorded on video and put online.
Compulsory courses (3-5 hp)
The basis for this research school is two compulsory courses per year for the students. The courses are progressive, i.e. the learning outcomes from the first course are a necessary requirement for the next course. The earlier courses are aimed at teaching important computational methods, while the later courses are aimed at relevant high-throughput methods for medical bioinformatics.
1. Applied Bioinformatics, 5 hp (Lars Arvestad, SU). In this course the students will be taught a good working habits for bioinformatics. They will learn to work in Unix, using Python for scientific code development and learn about good practices for scientific programming. Tentative maximum enrollment of 30 students. Next edition to run 28 May – 1 June 2018.
2. Algorithms in Bioinformatics, 5 hp (Lukas Käll, KTH). This course will provide an in depth understanding some of the most important algorithms used in bioinformatics. The students will learn how to apply fundamental algorithm design methodologies such as dynamic programming, clustering to problems in computational biology and bioinformatics. 23-27 October 2017.
3. Machine Learning in Medical Bioinformatics (Björn Wallner, LiU). In this course the students will learn statistical and machine learning methods that are widely used in medical bioinformatics today. June 11-15 2018.
4. Experimental design for high-throughput technologies (Carsten Daub, KI). In this important course the students will learn how to design the bioinformatics analysis of high throughput experiments. Given the background from the three earlier methods they should be able to design a pipeline that can easily be extended for more advanced analysis. Tentatively to run May 2018.
5. Integrative analysis of omics data using systems biology approaches (Erik Kristiansson, Chalmers). Here, the students will be taught how to analyse the results they have obtained from their bioinformatics pipeline and to integrate these with data from other experiments.
6. Variation interpretation and structural bioinformatics (Mauno Vihinen, LU). In this course the student will learn how to use information from personal genomics studies to interpret the effects of small and large variations. The students will also learn how to use structural bioinformatics tools predictions and analyses of variant effects and mechanisms.
Workshops (1 hp)
The second compulsory part of the research school is the annual workshop. In addition, to increasing the communication between the medical and informatics community the workshop is also an important part of the education of the Ph.D. students. The workshop will include
1. Training in presentation and writing skills.
2. Presentation of the projects by all of the students with individual feedback.
3. Individual mentoring by their bioinformatics mentor.
4. Invited keynote speakers giving talks about state of the art areas within medical bioinformatics.
In addition to the compulsory courses we believe there is a need for other advanced courses in bioinformatics. Each year we will open a call to the Swedish bioinformatics community to give courses and then after input from the Ph.D. students the board will select additional advanced courses. We expect that most of these courses will not be given every year.
There are of course many fine courses available outside the Research School, in Sweden, abroad, or online, which we encourage students to take as appropriate. Contact the Dean if you find one that you are interested in. Programming courses are important for first-year students who have not had them (or the equivalent experience). SciLifeLab offers courses — the Python may be particularly appropriate. Note that this programming course has a registration deadline of 11 September 2017. Some of the core courses require programming, and students are responsible for meeting all prerequisites in time to take courses.
- 2017 (Year 1 for first batch of students)
- Feb 28 Application deadline
- Mar 31 Start of research school
- June Applied Bioinformatics
- Aug 21-22 Annual meeting and workshop
- Oct 23-27 Algorithms in Bioinformatics
- 2018 (Year 2 for first batch of students)
- Mar Experimental design for high-throughput technologies
- June 11-15 Machine Learning in Medical Bioinformatics
- Aug Workshop
- Sep Integrative analysis of omics data using systems biology approaches
- 2019 (Year 3 for first batch of students)
- Jan Variation interpretation and structural bioinformatics
- Aug Workshop
One of the aspects of this program is to improve the supervision of the students. Here, we propose to use a modified version of the idea used in Gothenburg some time ago with two supervisors for each student, one bioinformatician and one medical scientist. Our goal is that this program each student will be assigned a mentor from the Swedish bioinformatics community. The mentor should be from another research constellation than the student. The role of the mentor will be to help the student identify and solve computational bottlenecks in their research project. The student will discuss with the mentor at least twice per year, either via electronic meetings or by short visits.
Finally, the student, the mentor and the supervisor will meet at the annual workshop, first individually and then later together with the supervisor to discuss the progress of the project.