2023-2024 / BIOL0030-1

Modeling dynamical biological systems

Duration

15h Th, 15h Mon. WS

Number of credits

 Master in bio-informatics and modelling (120 ECTS)3 crédits 
 Master in biology of organisms and ecology (120 ECTS)5 crédits 

Lecturer

Marilaure Grégoire, Patrick Meyer

Coordinator

Patrick Meyer

Language(s) of instruction

English language

Organisation and examination

Teaching in the first semester, review in January

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

Mathematical models are fundamental tools to understand how biological systems work and interact with the environment. Models are more and more used in many areas of applied ecology and genetic regulation. This lecture is targeted towards giving an introduction to ecological modelling accessible with limited mathematical and computational skills offering an overview of the state of the art of dynamical modelling. We will first define the modelling philosophy and introduce essential concepts for describing and analyzing ecological systems. Then, the students will learn to write the mass-balanced equations that govern dynamical systems, to translate in mathematical formalism ecological and chemical processes, to solve these equations in simplified conditions (e.g. steady state, prey-predator interactions, 2-species competition) and analyze model solution in a phase-plane. The lecture will involve practical work in R that will allow understanding and running (simple) model codes. Examples from the terrestrial, fresh water,  ocean systems and gene regulation will be selected.

Learning outcomes of the learning unit

The final aim is to lead the students to understand dynamical modeling and to be able to conceive and run simple models.

Prerequisite knowledge and skills

Basic R knowledge should have already been acquired  (for example through STAT0077 or OCEA02224 courses).

Planned learning activities and teaching methods

An important part of the course will be devoted to the implementation of very simple examples in order to get familiar with models implementation

Mode of delivery (face to face, distance learning, hybrid learning)

Face-to-face course


Additional information:

Presential classes, exercises on computers during the classes as well as as homeworks. 

All the lecture materials (including podcasts) are made available via eCampus. 

Recommended or required readings

A Practical guide to Ecological Modelling, Using R as a simulation Platform. Soetaert and Herman, 2009.
Ecological Dynamics, Gurney and Nisbet, 1998.

Exam(s) in session

Any session

- In-person

written exam ( open-ended questions )

Written work / report


Additional information:

Part Marilaure Grégoire: A written, in-person, examination will be organized in January.  This exam will not require the use of a computer. It will involve questions on the theory, practicals and homework.  

A homework  is due for January 7th at midnight. Description of the homework will be given during the lecture and will be made available via eCampus. Students will have to develop, implement and analyze a simple biogeochemical model to solve an environmental problem.  This homework has to be realized by group of 3-4 students. A written report of ~10 pages describing the results and answering a list of questions has to be provided as well as the Rmd file describing the model code. Questions on the homework will be part of the written exam.

For those who failed in January, a  second session exam will be planned in August/September. This second session exam will be similar to that organized in January. 

All the exams are exclusevely in person.

Part Patrick Meyer: a homework. 

Work placement(s)

Organisational remarks and main changes to the course

Contacts

Prof. Marilaure Grégoire,

MAST, ULg
e-mail : mgregoire@uliege.be 
tel : 04366 3354

******************

Prof. Patrick Meyer,

BioSys Lab
e-mail: Patrick.Meyer@uliege.be
tel : 04366 3030

Association of one or more MOOCs

There is no MOOC associated with this course.