Duration
150h Proj.
Number of credits
| Master of Science (MSc) in Biomedical Engineering | 5 crédits | |||
| Master of Science (MSc) in Computer Science and Engineering | 5 crédits | |||
| Master of Science (MSc) in Computer Science | 5 crédits |
Lecturer
Language(s) of instruction
English language
Organisation and examination
Teaching in the second semester
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
Students are provided with an active research problem that requires carrying out a detailed large-scale genomic analysis. The specifics of the research problem are provided by the supervisor or via ongoing collaborative efforts. This year will be about "epistasis networks" and how to use them to detect individual heterogeneity. Note that last year, the course focused on "epistasis" in general and narrowing the gap between statistical findings and biological relevance in particular.
Depending on the nature of the data students may opt for parametric or non-parametric analysis methods, statistical or machine learning based analytic tools. Any technique from previous courses is allowed, as long as it is appropriate for the problem at hand.
Given the interdisciplinary nature of the project work, students can work in groups of 2 or 3. Upon termination of the project, each individual prepares an individual report. There are no class sessions apart from one during which the project problem is introduced. Theoretical and practical guidance is offered upon request.
Learning outcomes of the learning unit
Given data, students are able to apply and reinforce acquired knowledge on a practical problem in statistical genetics. In particular, students are able to carry out a sound and detailed genetic association interaction analysis, with the most appropriate software tool at hand, covering the following aspect from the analysis pipeline: data cleansing, statistical analysis, interpretation, reporting.
Prerequisite knowledge and skills
A background in biostatistics, bioinformatics or statistical genetics is a pro. Alternatively, one has taken either one of the following courses: GBIO0002, GBIO0009, GBIO0030.
Planned learning activities and teaching methods
During a kick-off meeting, the problem and data are introduced. Students can use their own data upon agreement with the course responsible. Students can work alone (discouraged) or in groups of maximum three students. Several groups may work on the same or different real-life data set (depending upon availability). Supervision is provided via members of the BIO3 group at the GIGA or the EECS department of the School of Applied Sciences. Group meetings with the supervisors may be organized upon request. Upon termination of the project, each individual prepares a report and orally defends it.
Mode of delivery (face to face, distance learning, hybrid learning)
Primarily distance learning
Recommended or required readings
There is no mandatory textbook. Essential information will be posted on the website http://bio3.giga.ulg.ac.be/archana_bhardwaj/?Courses
Final grading is based on a report and its oral defense using the following 5 criteria:
- Ability to formulate the research problem and the context (introductions, data description)
- Presentation of the analysis workflow (methods, analysis section)
- Quality of the analysis (validity of results)
- Creative input (analytic tool, stuffing, conclusion section)
- Quality of the report and presentation slides
Work placement(s)
Organisational remarks and main changes to the course
The project work is organized in the second semester.
Exam in June
Depending on the number of students who enrol on this course, content and practical organization may be adapted, to maximize the experience in a multi-disciplinary environment.
Contacts
Kristel Van Steen - e-mail kristel.vansteen@uliege.be
Assistant: to be communicated
Preferred contact mode: e-mail (mention GBIO0031 in the subject title) or personal contact, after a lecture or by appointment. Online meetings when the COVID-19 situation requires doing so.