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Prospectus

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Computer Science: Bioinformatics

The Bioinformatics specialisation consists of a full-time, two-year master’s programme (120 EC).

Curriculum

Year 1&2

  1. The required Core component Bioinformatics (36 EC)

  2. Choice of one of the following two options:

  • Option 1: a selection of Specialisation courses and seminars (42 EC)

  • Option 2: a selection of Specialisation courses and seminars (24 EC) and the Introductory Research Project (18 EC)

Year 2

  1. The Master’s Thesis Research Project (42 EC )

    (including Master Class, Written Master's Thesis and Master's Thesis Presentation)

See also

For more information on the specific requirements of this specialisation, see the appendix of the Course and Examination Regulations.

More information

For specific questions about programme content, curriculum choices and/or study planning, please contact study advisor dr. Katy Wolstencroft through the Board of Bioinformatics (BoB).

For any other inquiries, please send an email to the Education coordinator.

Core component Bioinformatics (36 EC)

Important notes for students who started before 1 September 2020:

  • You can only take the new course Introduction to Deep Learning if you have not previously passed Neural Networks or Deep Learning and Neural Networks.

  • Students who started before 1 September 2019 are allowed to substitute at most two courses from the Core component Bioinformatics with Pattern Recognition and Functional Genomics and Systems Biology from the Technical University of Delft. The Support programme of 12 EC and the Research Assignment of 15 EC of previous academic years can be exchanged with the current specialisation courses and seminars. These changes should be applied for with the Board of Bioinformatics and with a proposal from the Bioinformatics study advisor sent to the Board of Examiners for approval.

Course EC Semester 1 Semester 2

Core component Bioinformatics (36 EC)

Advances in Data Mining 6
Computational Molecular Biology 6
Evolutionary Algorithms 6
Introduction to Deep Learning 6
Bio-Modeling 6
Image Analysis with Applications in Microscopy 6

Specialisation courses and seminars (42 EC)

Important notes for students who started before 1 September 2020:

  • The Introductory Research Project (18EC) is removed from the curriculum. Instead, you are encouraged to take specialisation courses worth 18 EC in total (e.g., three courses of 6 EC each). As a student who started before 1 September 2020, doing an Introductory Research Project (previously also known as Research Assignment) instead of taking courses will be allowed if you choose to.
Course EC Semester 1 Semester 2

Fall semester

Advanced Data Management for Data Analysis 6
Automated Machine Learning 6
Complex Networks (BM) 6
Introduction to Machine Learning 6
Multiscale Mathematical Biology (BM) 6
Quantum Algorithms 6
Seminar Swarm-based Computation with Applications in Bioinformatics 6
Social Network Analysis for Computer Scientists 6
Text Mining 6

Spring semester

Advances in Deep Learning 6
Metabolic Network Analysis (BM) 6
Multicriteria Optimization and Decision Analysis 6
Psychology of Programming 6
Reinforcement Learning 6

Research components

Important notes for students who started before 1 September 2020:

  • The Introductory Research Project (18EC) is removed from the curriculum. Instead, you are encouraged to take specialisation courses worth 18 EC in total (e.g., three courses of 6 EC each). As a student who started before 1 September 2020, doing an Introductory Research Project (previously also known as Research Assignment) instead of taking courses will be allowed if you choose to.
Course EC Semester 1 Semester 2
Master Class 0
Master's Thesis Research Project (CS) 42

Course levels

  • Level 100
    Introductory course, builds upon the level of the final pre-university education examination.
    Characteristics: teaching based on material in textbook or syllabus, pedagogically structured, with
    practice material and mock examinations; supervised workgroups; emphasis on study material and
    examples in lectures.

  • Level 200
    Course of an introductory nature, no specific prior knowledge but experience of independent
    study expected.
    Characteristics: textbooks or other study material of a more or less introductory nature; lectures, e.g. in
    the form of capita selecta; independent study of the material is expected.

  • Level 300
    Advanced course (entry requirement level 100 or 200).
    Characteristics: textbooks that have not necessarily been written for educational purposes; independent
    study of the examination material; in examinations independent application of the study material to
    new problems.

  • Level 400
    Specialised course (entry requirement level 200 or 300).
    Characteristics: alongside a textbook, use of specialist literature (scientific articles); assessment in the
    form of limited research, a lecture or a written paper. Courses at this level can, to a certain extent, also
    be on the master’s curriculum.

  • Level 500 Course with an academic focus (entry requirement: the student has been admitted to a
    master’s programme; preparatory course at level 300 or 400 has been followed).
    Characteristics: study of advanced specialised scientific literature intended for researchers; focus of the
    examination is solving a problem in a lecture and/or paper or own research, following independent
    critical assessment of the material.

  • Level 600
    Very specialised course (entry requirement level 400 or 500)
    Characteristics: current scientific articles; latest scientific developments; independent contribution (dissertation research) dealing with an as yet unsolved problem, with verbal presentation.

The classification is based on the Framework Document Leiden Register of Study Programmes.

Career Perspective