CourseSpecifications
Valid as from the academic year 2024-2025

Integrative Biology (C004000)

Course size
Credits 3.0(nominal values; actual values may depend on programme)
Study time 80 h

Course offerings and teaching methods in academic year 2024-2025
A (semester 2)
EnglishGent

Lecturers in academic year 2024-2025
Marchal, Kathleen

lectureseminar

WE09

Offered in the following programmes in 2024-2025
Bridging Programme Master of Science in Bioinformatics(main subject Engineering)
Master of Science in Bioinformatics(main subject Bioscience Engineering)
Master of Science in Bioinformatics(main subject Engineering)
Master of Science in Bioinformatics(main subject Systems Biology)
Master of Science in Bioscience Engineering: Cell and Gene Biotechnology
Exchange Programme in Bioinformatics (master's level)

lecturer-in-charge
crdts
33
33
3
3

offering
AAA
A
AA

Teaching languages
EnglishKeywords
Network-based data analysis, systems biology, data-integration
Position of the course
This is an advanced course in the master of bioinformatics and systems biology which aims atintroducing the importance of data-integration in systems biology. The course is tailored
towards students that pursue a master in bioinformatics or any other advanced master thataims at the analysis of cellular, molecular data. The course aims at showing how in systems
biology specific biological questions are solved through data-integration. The course will
highlight some state-of-the-art research questions and show how they can be approachedusing bioinformatics tools of which the underlying methods are taught in the theoreticalcourses. The main emphasis is by means of examples showing that the choice of the analysis
method can severely influence the outcome of the results and that therefore in bioinformatics
both understanding the intricacies of the biological problem and the underlying assumptions of
the tool used to solve the problem are essential to critically evaluate the results. It also shows
how different tools solve slightly different research questions and how users need to be awareof the intricacies of the tool to select to most optimal tool for a given research question. By
giving examples of applications of integrative data analysis in real world (in plant breeding,synthetic biology, personalized medicine) students will be informed on the ethical aspects thatgo hand in hand with this novel domain of data-(re)analysis.
Contents
The course integrates tools and techniques discussed in the other courses to solve specific‘biological problems’ in bioinformatics.
Part II (semester II)
Top down network inference• Expression based methods• Integrative methods
Network-based data-interpretation• Overview of techniques to visualize data on a network (Pathfinding approaches, Graphbased clustering, diffusion techniques)(Approved)1• Application: eQTL analysis, gene prioritization, biomarker identification
Genotype phenotyping mapping• GWAS/QTL (population stratification, linear models)• Network-aided GWAS
• Integrative genotype-phenotype mapping (cancer systems genetics)
Applications in the domain of medical, microbial and Biotechnology (plant breeding,GWAS for trait selection, personalized medicine)
Initial competences
identical to those of the Master in Bioinformatics
Final competences
1 Understanding the concepts of network inference, motif detection, data integration.
2 Recognize analysis techniques underlying bioinformatics tools.
3 Being able to independently read and analyse a systems biology paper that combines
1 biological results with advanced data-analysis.
4 Being able to apply a tool given the available documentation and literature.
5 Being able to implement a tool given the description in a paper.
6 Being able to construct a model to understand a complex biological problem.
7 Critical reading attitude towards the domain.
8 Understanding bioinformatics is a fastly evolving discipline.
9 Functioning as a member of a multidisciplinaire environment.
10 Communication in an interdisciplinary context.
11 Being aware of ethical and confidentionality aspects of some bioinformatics applications.
Conditions for credit contract
Access to this course unit via a credit contract is determined after successful competences assessment
Conditions for exam contract
This course unit cannot be taken via an exam contract
Teaching methods
Seminar, Lecture
Study material
Type: Slides
Name: Marchal_notes
Indicative price: Free or paid by faculty
Optional: noLanguage : English
Number of Slides : 100
Available on Ufora : Yes
Online Available : Yes
Available in the Library : No
Available through Student Association : No
Additional information: cursus materiaal is online available and freeReferences
recent research articles
Course content-related study coaching
Assessment moments
end-of-term and continuous assessment
Examination methods in case of periodic assessment during the first examination period
Written assessment with open-ended questions, Written assessment
Examination methods in case of periodic assessment during the second examination period
Written assessment
Examination methods in case of permanent assessment
Assignment
Possibilities of retake in case of permanent assessment
not applicable
Extra information on the examination methods(Approved)2--- Klik om te editeren --The exam is open book if in takes place on line
In principle the use of generative AI during the exam is forbidden. However because it is
impossible to check this, answers that are correct but do not use any concepts or terminologyof the course will be judged anyhow incorrect. This will be told in advance to the students. The
link in the answer to the lecture should be clear. If the students wishes to add more information
than was told in the course, the source of the inormation should be mentioned.
Calculation of the examination markStudents will be evaluated based on the written end exam (open book) for their understanding,analytical and synthesizing skills (18/20). Student will have to write a report (review of a paper,permanente evaluatie). THis will contribute 3/20 marks.

(Approved)3