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Bioinformatics for Translational Medicine: exome and RNA sequencing

Bioinformatics for Translational Medicine

  • Master Bioinformatics and Systems Biology
  • VU
  • Admin. code FDBA
  • Studielast 6 EC

Course objective

Observations from biological high-throughput experiments will allow us to improve diagnosis and give a personalised treatment plan for patients. However, integrating data from several sources and using this data for predictions is non-trivial.
This is a theoretical and practical Bioinformatics course on computational methods for Translational Medicine; we will focus on Bioinformatics algorithms that are used to predict the clinical outcome for patients and analysis methods to obtain deeper understanding of complex diseases, by combining data from various high-throughput experiments such as proteomics, microarrays and next-generation sequencing as well as existing biological databases.

Next Generation Sequencing: Exome sequencing and RNA-seq

Next Generation Sequencing (NGS) allows a range of applications. Two of these applications are exome sequencing and RNAseq. With exome sequencing we aim to detect variants that cause rare disorders. RNAseq is used for gene expression studies. You will be introduced to Next Generation Sequencing after which we will explain exome sequencing and RNAseq in detail. In the computer labs you will be able to try it yourself.



  • Free University.
    • All lectures are in WN-P647, on the sixth floor in the W&N building.


Lectures + computer lab

Exome sequencing

The story of Nicholas Volker


Topic revision: r24 - 27 May 2020, UnknownUser Search
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