NBIA07023U Bioinformatics of High Throughput Analyses

The student will achieve the following from attending the course:

Knowledge:

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.

Skills:

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.

Competences:

• 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.