Big Data in Biomedical Sciences

2019-2020

Course Objective

Students will learn how various types of biomedical data are acquired,
how they can be used in fundamental and translational research, and in
which format they are usually stored.
Students will have knowledge of the FAIR principles (Findable,
Accessible, Interoperable, Reusable) for data storage.
Student will understand the value of accurate and understandable
metadata and feel responsible for good 'data stewardship'.
Students oversee the potential and current challenges of big data
applications in personalized medicine, genetics, neuroscience,
connectomics and metagenomics.
Students have hands-on experience with programming algorithms for big
data mining or other bioinformatics analyses.
Students have sufficient insight into bioinformatics workflows,
possibilities and limitations to effectively communicate with
bioinformaticians.
Students can independently collect up-to-date knowledge on the above
topics ('metalearning'). This is important because bioinformatics is a
fast-changing discipline.

Course Content

This elective addresses important concepts in bioinformatics and big
data mining, with powerful applications in biomedical sciences. Lectures
and practical assignments provide theory and hands-on experience in fast
moving fields of personalized medicine, genetics, neuroscience,
connectomics and metagenomics.

Teaching Methods

Each week the course will offer lectures (35 h for the entire course)
and a practical computer assignment (16 h).
Expect to spend approximately 100 h on self-study.

Method of Assessment

The knowledge in the lectures will be tested by a written exam with open
questions held at the end of the course.
Each practical assignment will be evaluated individually by the
teachers. The criteria for grading will be made accessible in the form
of 'Rubrics' in Canvas.
The final grade will be calculated as 60% (final exam) and 40%
(assignments).
To pass the course, both the exam and assignments need to be graded 5.5
or higher.

Literature

Please see instructions on Canvas

Target Audience

Accessible to the BSc Biomedical Sciences or the BSc Health & Life.

Additional Information

This elective is related to the learning track Bioinformatics.
It is highly recommended in preparation for the following minors:
Bioinformatics & Systems Biology,
Personalized Medicine,
Biomolecular & Neurosciences track Neurosciences
Research minor: Science in Medicine

Explanation Canvas

The up-to-date course schedule will be available on Canvas

General Information

Course Code AB_1256
Credits 6 EC
Period P5
Course Level 200
Language of Tuition English
Faculty Faculty of Science
Course Coordinator dr. ir. A.J.A. Groffen
Examiner dr. ir. A.J.A. Groffen
Teaching Staff dr. ir. A.J.A. Groffen
dr. D. Molenaar
prof. dr. B. Teusink

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Lecture, Study Group, Practical
Target audiences

This course is also available as: