Principles of Bioinformatics


Course Objective

Are you interested in bioinformatics? Would you like know how huge
amounts of data can be analysed in order to discover new biology? Would
you like to solve open questions in scientific research?
This course is open for any Bachelor student in a Science Degree
(including Biology or Biochemistry).

Principles of Bioinformatics is the starting course for bioinformatics
at an Academic level. It aims to give a broad overview of important
topics relevant to the field, with a focus on current (open) problems in
bioinformatics research.
During the lectures and practical sessions you will become familiar
with practical solutions, but also discover that there is still a lot of
room for improvement in this rapidly advancing field of research.


• To make the students aware of gaps in their own background knowledge.
• The student will be aware of the major issues, methodology and
available algorithms in bioinformatics.
• To work together in a group of diverse backgrounds.
• To gain hands-on experience in scripting and handling basic
mathematical equations as a means of solving bioinformatics problems.
• To develop a basic understanding of major concepts in genomics and
molecular cell biology or to develop a basic scripting skills in python
that are relevant to current topics in

Course Content

• Evolution, Genomes, Sequences, Biomolecular Structure, Biological
Databases BLAST & PSI-BLAST, Protein domains & evolution, Next
Generation Sequencing (NGS) or Massively Parallel Sequencing (MPS) and

There are practicals sessions that aim to show you both existing
solutions as well as open problems within the field of Bioinformatics.
In the practicals
you use existing databases and (web-server) solutions to solve
biological problems. You
will also use python scripts to automate queries to databases and web
servers to
investigate the value of current Bioinformatics Algorithms.

The following topics are covered:
• A short introduction to Python
• Data resources in for the Life Sciences, including: Gene Ontology
Database (GO), Pfam and SCOP
• Homology Searching ( BLAST / PSI-BLAST )
• Dynamic Programming
• Benchmarking
• Computational Analysis of Genome Sequencing (Genome Assembly)
• Recent research in Bioinformatics

Teaching Methods

• 10 Lectures (two hour lecture in the morning, two days per week)
• 12 Practical sessions (two hour sessions following the morning
lectures, two days per week), partially supervised.

Method of Assessment

• [50%] Assignments (4 graded assignments)
• [50%] Oral or written exam (depending on number of course students) to
assess:exercises, topics covered by the project and lecture topics


• Course material (slides, scientific papers) on canvas
Essential Bioinformatics methods are covered by the following books:
• Essential Bioinformatics, Jin Xiong, Cambridge University Press,
ISBN978-0-521-60082-8 (this is a very basic book, for BSc level only)
• Marketa Zvelebil and Jeremy O. Baum Understanding Bioinformatics
Garland Science 2008 ISBN-10: 0-8153-4024-9 (if you are planning to take
any further courses in bioinformatics, we would advise you to get this

Target Audience

3CS, 3IMM, 3LI and:

Additional Information

This course is part of the Minor Bioinformatics and Systems Biology

Depending on the number of students, a large part of this course may be
given together with the MSc course "Fundamentals of Bioinformatics". The
assessment is at third year BSc level.

This course is open for any Bachelor student in a Science Degree
(including Biology or Biochemistry).

Recommended background knowledge

An interest in programming and biological problems.

General Information

Course Code X_401094
Credits 6 EC
Period P1
Course Level 300
Language of Tuition English
Faculty Faculty of Science
Course Coordinator dr. S. Abeln
Examiner dr. S. Abeln
Teaching Staff prof. dr. J. Heringa
L. Hoekstra
G.R. van der Ploeg BSc
A.S. Rauh BSc
P. Schmidt

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Lecture, Computer lab, Practical
Target audiences

This course is also available as: