Study-Unit Description

Study-Unit Description


CODE FEH5100

 
TITLE Modelling Techniques in Health Sciences

 
LEVEL 05 - Postgraduate Modular Diploma or Degree Course

 
ECTS CREDITS 5

 
DEPARTMENT Food Sciences and Nutrition

 
DESCRIPTION This study-unit is divided in three main sections, namely; reaction kinetic modelling, molecular modelling and applied statistics. This is to introduce research students to the most modern techniques used in the Food Sciences. More specifically:
- Section 1 will introduce the students to the principles of experimental designs data (pre)processing for analysis of food microbiology and chemistry data. It will also address issues on kinetic modelling in relation to chemical, biological and enzymatic reaction kinetics. The difference between stochastic and deterministic modelling will be described and their application in the area of predictive microbiology (software applications and simulations) will be presented.
- Section 2 will introduce the students to molecular modelling and how it can be used in Food Sciences to measure chemical and thermodynamic interactions such as molecular aspects of the lipid protein interactions. This section will focus on empirical simulations, for systems under static and dynamic conditions. The students will also be introduced on how to use molecular modelling software such as Lammps.
- Section 3 will introduce the students to the principles of multivariate analysis and their application in analysing microbial and quality data in Food Science.

Study-unit Aims:

The main aim of this study-unit is to introduce students to advanced techniques of mathematics and statistics in order to interpret and simulate the microbiological responses taking place during static and dynamic processing environments.

This study-unit also aims at giving students the opportunity to learn how to develop skills in molecular modelling to simulate the responses of biological substances in specific environments representing food structures and to use applied statistics including multivariate analysis.

Learning Outcomes:

1. Knowledge & Understanding:

By the end of the study-unit the student will be able to:
- Identify the appropriate modelling technique to solve specific problems;
- Demonstrate an understanding of the kinetics and molecular modelling in Food Science;
- Analyse and evaluate data that is relevant to Food Safety and Food Preservation;
- Recognise and tackle problems whose solution is facilitated by the application of modelling.

2. Skills:

By the end of the study-unit the student will be able to:
- Describe and critically review existing models as well as develop and employ new models that can contribute to the interpretation of Food Processing and Food Preservation phenomena;
- Develop modelling skills for interpreting experimental data in Food Science;
- Operate simulation studies by using different models with biological interpretation.

Main Text/s and any supplementary readings:

- Progress on Quantitative Approaches of Thermal Food Processing, edt. Vasilis Valdramidis, Jan Van Impe (Nova publishers), 2012.
- Andrew R. Leach. Molecular Modelling: Principles and Applications (2nd edition), Prentice-Hall, (2001). ISBN: 0582382106

 
STUDY-UNIT TYPE Lecture, Independent Study & Tutorial

 
METHOD OF ASSESSMENT
Assessment Component/s Assessment Due Resit Availability Weighting
Oral Examination (15 Minutes) SEM1 No 20%
Presentation (30 Minutes) SEM1 No 30%
Assignment SEM1 Yes 50%

 
LECTURER/S Ruben Gatt
Vasileios Valdramidis

 
The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the description above applies to study-units available during the academic year 2020/1. It may be subject to change in subsequent years.

https://www.um.edu.mt/course/studyunit