NBIA07023U Bioinformatics of High Throughput Analyses
MSc Programme in Molecular Biomedicine
MSc Programme in Bioinformatics
MSc Programme in Biology
MSc Programme in Biology w. minor subject
There are four major subject areas of the course:
- Usage of R in applied statistics and data handling: This will be used throughout the course
- Visualization, handling and analysis of genomic data using the genome browser, the galaxy tool and R
- Expression analysis using microarrays and DNA sequencer data (”tag data”) using R and public tools
- Analysis of proteomics data using R and public tools.
The student will achieve the following from attending the
After successfully completing the course, students will master the fundamentals of computational analysis of large biological datasets. This includes:
i) understanding the diverse laboratory techniques and biological processes generating the data
ii) understanding and mastering the statistical and informatics techniques used for visualization and analysis, including the selection of appropriate techniques for a given data and question
iii) interpreting analysis results in a biological context, and identify and apply follow-up analyses based on this.
The skill set taught in the course can be divided into:
- Applied statistics, visualization and data handling within R and the Galaxy web tool
- Knowledge of molecular biology techniques that generate genomics data - cDNA analysis, ChIP, RNA-seq, microarrays, mass spec and more, and their strengths and weaknesses
- Visualization techniques for the data above: genome browsers and R
- Techniques for data mining and data exploration
There is a special focus on hands-on exercises to develop analysis skills; both within lessons, group work and in the final evaluation. We also have one day with speakers from industry that use similar techniques.
- To be able to analyze, visualize and interpret cutting edge biological data sets using biological and statistical toolsets combined.
- To solve realistic problems in which finding the appropriate methods - and the specific programming syntax necessary - for attacking sub-questions question is an important part of the problem.
- 7,5 ECTS
- Type of assessment
- Written assignment, 5 daysOral examination, 30 minutes (no preparation time)---
- Exam registration requirements
In order to be allowed to the final exam, the student must have had three smaller written group projects approved.
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners/co-examiners
As ordinary exam.
The three smaller written group projects have to be approved not later than 2 weeks before the reexam.
Criteria for exam assesment
To obtain the grade 12:
- The student must be able to explain the motivation, biological relevance and use of the methods covered in the course.
- The student must be able to understand and critically assess relevant scientific literature.
- The student must demonstrate expertise in the tools used in the course.
- The student must be able to suggest which methods and programs to apply for a given biological problem, and to point out problems and difficulties relating to such applications.
- Analogously, the student must be able to understand the strengths and weaknesses of different biological data types.
- The student must, with the help of program documentation and lecture material, be able to identify the methods that are appropriate and the syntax necessary for solving problems.
- The student must be able to after analysis interpret the analysis outcome in a biological setting, and identify and apply relevant follow up-analyses or extensions.
- Practical exercises
- Project work