Duration
25h Th, 15h Pr, 35h Proj.
Number of credits
Lecturer
Language(s) of instruction
English language
Organisation and examination
Teaching in the first semester, review in January
Schedule
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 may 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
- Microbiome and systems health
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.
This course contributes to the learning outcomes I.1, I.2, II.1, II.2, II.3, III.1, III.2, III.3, IV.1, VI.1, VI.2, VII.1, VII.2, VII.3, VII.4 of the MSc in computer science and engineering.
Prerequisite knowledge and skills
The course requires a good knowledge of biomedicine or informatics as well as statistics. This course builds on GBIO0002.
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 and following their practical work.
The practical aspects of the course involve the following:
- students are given analysis protocols related to the course topics (see before)
- via group work, (pieces of) analysis protocols are implemented and applied to real-life data
- made efforts are discussed in class and results of applied work are presented
- guidelines regarding the latter presentations will serve as homework assignment
- at the end of the course, analysis pipeline pieces will be glued together to constitute a single workable analysis flow
The aforementioned homework scheme may be adapted, when the number of students is too small (<6).
Mode of delivery (face to face, distance learning, hybrid learning)
In-person or online (depending on COVID-19 evolutions).
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
http://bio3.giga.ulg.ac.be/archana_bhardwaj/?Courses
Students are assessed via assignments and on the basis of an oral exam in the first session. The oral exam is open book and may cover material from both the theoretical and practical sessions.
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 part of the assignments for which they performed worst and hand in a written report.
Work placement(s)
Organisational remarks and main changes to the course
Language: English
Please consult the course website for practical and more detailed information, including course note material and homework assignments.
Contacts
Kristel Van Steen - e-mail kristel.vansteen@uliege.be
Preferred contact mode: e-mail (include GBIO0009 in the subject title) or personal contact after a lecture or by appointment. Online contacts when COVID-19 imposes to do so.