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Biological and Biomedical Informatics


Admission requirements

Core course in MSc Bioinformatics and MSc Life Science and Technology, elective course MSc Chemistry

Assumed/Recommended prior knowledge

Students should be familiar with fundamental concepts in molecular biology. Programming experience is useful, but not required.


The course will cover the methods, algorithms and practical aspects of bioinformatics for omics data analysis, with a particular focus on human health and disease. The following topics will be covered:

a) bioinformatics data resources (global and FAIR data sharing for omics data)
b) computational analyses of genomic data (genome sequencing approaches, genome assembly, de novo sequencing, resequencing and variation analysis),
c) computational analyses of RNA and protein data (RNA-Seq and microarray analyses, RNOmics, pathway analysis, functional enrichment/over-representation and protein-protein interaction networks)
d) medical informatics (computational analyses of omics data in rare and complex disease studies, principles and problems for managing and sharing patient data)

Course objectives

At the end of the course, students will be able to:

  1. Make use of global public bioinformatics data resources, identifying and linking data to answer biomedical research questions
  2. Explain the FAIR data principles (i.e. that data should be Findable, Accessible, Interoperable and Reusable) and the role FAIR plays in data reuse and reproducibility
  3. Discriminate between different approaches to analysing genomic and transcriptomics data (in the context of the data and research question)
  4. Discriminate between different approaches to “downstream analyses” – using structured knowledge resources, such as ontologies and biological pathway databases, to interpret omics results
  5. Explain the consequence and significance of the genomic revolution on biomedical research and human health
  6. Design and execute a bioinformatics workflow to analyse and evaluate the consequences of genomic variants from an individual
  7. Critically assess published peer-reviewed research by reanalysing and evaluating results against the original outcomes


The most recent timetable can be found at the Computer Science (MSc) student website.

You will find the timetables for all courses and degree programmes of Leiden University in the tool MyTimetable (login). Any teaching activities that you have sucessfully registered for in MyStudyMap will automatically be displayed in MyTimeTable. Any timetables that you add manually, will be saved and automatically displayed the next time you sign in.

MyTimetable allows you to integrate your timetable with your calendar apps such as Outlook, Google Calendar, Apple Calendar and other calendar apps on your smartphone. Any timetable changes will be automatically synced with your calendar. If you wish, you can also receive an email notification of the change. You can turn notifications on in ‘Settings’ (after login).

For more information, watch the video or go the the 'help-page' in MyTimetable. Please note: Joint Degree students Leiden/Delft have to merge their two different timetables into one. This video explains how to do this.

Mode of instruction

Lectures, practical classes, research paper seminars and assignments.

Assessment method

The course will be assessed by written examination (50%) and two practical assignments (25% each).

The examination contains material from the lectures, practical classes and seminars. It will assess objectives 2-5.

Assignment 1: Development of a scientific workflow to analyse, prioritise and interpret variant data from an individual human genome (25%). This assignment will assess the course objectives 1, 3, 6 and 7

Assignment 2: Reanalysing published omics data (25%). This assignment will assess objectives 1, 2, and 7. You will need to critically assess your results against those published, to determine your confidence in the original findings and limitations in the study design, reproducibility and FAIRness.

In order to pass the course, marks for the exam and combined assignments must be at least 5.5.

Students will be permitted to retake one of the two assignments during the exam retake period if they do not receive a passing grade during the course.

Reading list

  • Current bioinformatics literature referenced in the lectures and practical sessions


From the academic year 2022-2023 on every student has to register for courses with the new enrollment tool MyStudyMap. There are two registration periods per year: registration for the fall semester opens in July and registration for the spring semester opens in December. Please see this page for more information.

Please note that it is compulsory to both preregister and confirm your participation for every exam and retake. Not being registered for a course means that you are not allowed to participate in the final exam of the course. Confirming your exam participation is possible until ten days before the exam.

Extensive FAQ's on MyStudymap can be found here.