25h Th, 15h Pr, 35h Proj.
Number of credits
|Master in data science (120 ECTS)||5 crédits|
|Master of science in computer science and engineering (120 ECTS)||5 crédits|
|Master in data science and engineering (120 ECTS)||5 crédits|
|Master in computer science (120 ECTS)||5 crédits|
Language(s) of instruction
Organisation and examination
Teaching in the first semester, review in January
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
In this course an introduction to the bioinformatics discipline is given. We do so by introducing the students to several subtopics corresponding to different research questions. These include, but are not restricted to:
- Genetic mapping
- Post-GWAS bioinformatics
- Molecular subtyping of patients towards personalized medicine
- The interactome as key component of systems medicine
- Networks to support systems biology
The content of the course may be adapted during the course of the year, depending on the need to spend more time on particular subtopics and the interests of the students.
Learning outcomes of the learning unit
At the end of the course, students have an idea about what bioinformatics in a medical context entails as a profession. Since this course is an introductory course, students will be evaluated about key concepts related to each subtopic, rather than in-depth understanding of each subfield.
Prerequisite knowledge and skills
The course requires a good knowledge of biomedicine or informatics.
Planned learning activities and teaching methods
The course mainly involves interactive sessions, where discussions in the more theoretical oriented classes emerge from the input given by the students. The exercise sessions allow students to see how software tools, related to the discussed research questions, are used and how their output needs to be interpreted. A few classes will be dedicated to invited speakers, who will talk about their areas of bioinformatics.
Regarding the homework assignments, three homework styles may be presented: 1) literature-based (i.e., discussing a paper related to the class topic); 2) programming-based (i.e., targeting students with a strong informatics background); 3) classic style (i.e., questions-answers type of homework). Students can work in groups but should select at least 2 styles throughout the course and at least once a literature-based homework. The latter are presented and discussed in class, to further clarify concepts covered during the theoretical or practical course sessions.
The aforementioned homework scheme will be adapted, when the number of students is too small (<6).
Mode of delivery (face-to-face ; distance-learning)
Recommended or required readings
Since a variety of « hot » topics are covered, there is no single textbook. Useful references will be given as the course progresses.
All course material is posted on the course website, which can be accessed via
Assessment methods and criteria
Students are assessed via homework assignments and on the basis of an oral exam in the first session. Submitting all homework assignments in time is essential to pass this course, as well as having taken the exam.
In the second session, students will need to redo the homework for which they performed worst, as well as take an oral examination.
The oral exams are open book and may cover material from both the theoretical and practical sessions.
Please consult the course website for practical and more detailed information, including course note material and homework assignments.
Kristel Van Steen - e-mail email@example.com
Archana Bhardwaj - A.Bhardwaj@uliege.be
Preferred contact mode: e-mail A.Bhardwaj@uliege.be (include GBIO0009 in the subject title) or personal contact after a lecture or by appointment