Course: Theory of Bio-Informatics 1 credits: 3

Course code
Theory of Bio-Informatics 1
Study year
ECTS credits
M. Herber
Modes of delivery
  • Lecture
  • Tutorial
  • Theory of Bio-Informatics 1 - Computer, organised by STAD examinations

Learning outcomes

You will learn about the following concepts and techniques, and how to apply them to real-life datasets and problems:

  • The uses of Next Generations Sequencing (NGS) in modern experimental design
  • Next Generation Sequencers: Illumina HiSeq, PacBio, MinION; how they work and the data the generate
  • Protein structure & feature conservation
  • Alignment of 2 sequences using ClustalO and an appreciation of the underlying concept; use via the EBI website
  • Fast alignment of NGS data: mappers such as bowtie2 and BWA: how they work conceptually and houw they can be used from Galaxy
  • Downstream analysis of NGS alignment/mapping results; file types and pipelines in Galaxy
  • SNP and indel calling in alignment data; statistics, software and embedding in Galaxy


Bioinformatics is built on two great assumptions: that evolutionary relationships between proteins will show up in the DNA sequence coding for them, and that you can use these relationships in bulk to predict the likelihood that any 2 or more novel sequences are related. These two assumptions allow you to create alignments between wildly different DNA and protein sequences which allow you to compare them base by base or amino-acid by amino-acid with statistical confidence. From these alignments you can then infer whether mutations have occurred which affect the function of the protein in some way. Because Next Generation Sequencing produces such large amounts of data, new alignment methods have been developed which trade accuracy for speed. This course will introduce both the theory and practice of sequence alignment for inferring function, aligning reads from NGS and using these alignments to draw biological conclusions.

Literature: Introduction to Bioinformatics 4th Edition. ISBN-13:978-0199651566


  • Institute for Life Science & Technology