EZO-23306 Modelling Biological Systems

Course

Credits 6.00

Language of instruction:

Lectures in Dutch; written materials in English

Assumed knowledge on:

Modelling biological systems builds on first year biology courses, especially ecology, mathematics, statistics and physics. This basic knowledge is needed to adequately handle the models in the current course.

Continuation courses:

The following courses can be considered as a continuation of the learning outcomes of the present course: modelling biological systems II (SSB30806); concepts and approaches in
developmental biology (EZO22306); functional zoology (EZO30806); systems analysis, simulation and systems management (PPS20306); population and systems ecology (CSA20806);
programming in python (INF22306). Details on these courses can be found in the study guide.

Contents:

“Now more than ever, biology has the potential to contribute practical solutions to many of the major challenges confronting the . . . world. [The National Research Council] recommends that a ‘New Biology’ approach—one that depends on greater integration within biology, and closer collaboration with physical, computational, and earth scientists, mathematicians and engineers—be used to find solutions to four key societal needs: sustainable food production, ecosystem restoration, optimized biofuel production, and improvement in human health.”

This quotation from the report ‘A new biology for the 21st century’ of the USA National Research Council (2009) puts quite a responsibility on the shoulders of future biologists. The
Wageningen Biology programme realises this responsibility by stating the following in its 2015 critical reflection.

“Understanding the complexity of biological systems, at scales ranging from single molecules to whole ecosystems, provides a unique intellectual challenge. The biosciences aim to understand living systems and preserve biodiversity and our environment, whilst simultaneously enabling us to produce sufficient, healthy, and safe food. The BSc Biology programme focuses on the functioning and complexity of living systems and the interactions with their (a-)biotic environment.”

Biological systems are arguably the most complex systems science tries to understand. We make observations, and try to obtain useful insight in the system. This requires hypotheses;
ideas of how we believe the world around us is structured and operates. Models translate our hypotheses into concrete predictions about our objects of study that can be tested by targeted
experiments.

The more complex the systems we study, the more crucial the use of models. There is a key role for one of the strongest tools in our scientific toolkit: mathematics. Mathematics are able
to capture complexity in a form that makes it manageable. Mathematical models allow a full exploration of the consequences of our hypotheses and provide quantitative, and therefore
precisely testable, predictions. Nowadays, this modelling toolkit is vastly extended by the wide availability of computers, which allow us to implement and test mathematical models, or even
directly simulate the behaviour of complex systems.

In this course we attempt to convey the fascination for biological systems and introduce the tools to model them.

Learning outcomes:

After successful completion of this course students are expected to be able to:
- identify the key components of a relatively complex biological system;
- draw a simplified graphical representation of a complex biological system;
- write down the mathematical equations governing this graphical representation;
- analyse the system of governing equations to make predictions about the biological system;
- write a simple computer program in python to simulate the simplified biological system;
- interpret the predictions and simulations of biological systems.

Activities:

Lectures and tutorials
Mondays start with a toolbox lecture, that introduces a new set of modelling tools. The second half of the Monday morning is reserved to read and study the lecture notes in the reader to prepare for the Tuesday toolbox exercise.

During the first half of the Tuesday morning, you make toolbox exercises to practice the tools. After the toolbox exercises, the Tuesday’s application lectures show you how the tools can be applied to a biological system.

During the rest of the week’s tutorials (so-called case exercises on Wednesday and Thursday), you work on more comprehensive examples. Practical examples comprise both paper and
pencil exercises, development and analysis of models or model equations, programming (in python), and studying and interpreting the results. All tutorials are supervised by lecturers
and assistants.

Each week is closed on Thursdays with a self-assessment, question party and discussion during the second half of the morning. The answers to the exercises become available, and you can self-assess your work. Then you are asked to create a reception-like setting. You find a peer, introduce yourself, and ask each other (still unanswered) questions about that week. Questions that cannot be answered by peers should be written down on post-its. These questions are collected, and discussed by a lecturer in a concluding plenary closure of the week.

Reports on toolbox and case exercises.
You deliver one report with motivated answers to the toolbox and case exercises before 10.30 h at each Thursday morning through Black Board. At 10.30 h at each Thursday the answers to the exercises are published on BlackBoard for self-assessment. The reports may be prepared in couples, but must be handed in individually. Please use the following naming convention for your report name to facilitate the evaluation: report_groupgroupnumber_fullname.docx.

Examination:

The course is ‘successfully completed’ if your final mark is sufficient (a non-rounded mark of 5.50 points or more out of 10). Your final mark is calculated from two components: your mark for the reports, to be handed in during the course, and your mark for the written exam at the end of the course. All learning outcomes are assessed in the weekly reports, and the final written exam.

Mark for the reports
Every week you work on a toolbox exercise and a case exercise. You are given the opportunity to hand in your reports on those exercises and the reports that are handed in correctly and on time will be judged. The average mark of all six sets of toolbox/case reports will be determined and this is your ‘report mark’.

Mark for the written exam
The 3 hours closed book exam at the end of the course consists of multiple choice questions about the content presented in the lectures, in the reader, and practiced during the toolbox and case exercises. If your mark is above 5.5, you successfully pass the course. If your mark is between 5.0 and 5.5, you may pass the course depending on the mark for your reports. If the mark for your written exam is lower than 5.0, you have to do a re-exam.

In case your report mark is higher than your mark for the written exam, your final mark is determined for 20% by your report mark and for 80% by your mark for the written exam. In case your report mark is lower than your mark for the written exam, your final mark is the same as your mark for the written exam.

Literature:

A manual presenting the contents of the course and the exercises for the tutorials.