Modeling of Physical-Chemical Processes in Biology

Course objectives

·              The teaching method is based beyond the classical lectures in the learning process of problem / topic, where students are asked to implement, in groups, specific applications that they will choose, combining individual study with the ability to search and compile information within collaboration. In small groups.

·              The teaching is initially done with lectures on the basic concepts to all students, then students ate divided into groups (with a small number of people). Each group is unsigned with the implementation of a specific problem of modeling in the field of Biology.

·              The course aims to familiarize students with the natural laws governing biological systems and how they can be used to model processes through:

·   the development of the appropriate mathematical model.

·   the implementation (or use) of software to solve the model

·   the extraction of information, with simultaneous evaluation and export of proposals for redesign of the whole process.

 

Examples of modeling physicochemical properties and processes that you modify in the course include:

·   Measures of hydrophobicity.

Modeling of Ligand-macromolecular interactions.

·   Examples of computer–aided drug design, CADD

·   Population models (e.x. Predator-Pray)

·   Epidemiology models (e.x. SIR Susceptibles, Infectives, Removed)

·   Dynamic models in systems biology and neuroscience

·   Basic mathematical tools: Linear Algebra, numerical analysis, stochastic processes, stability analysis.

 

Learning Outcomes

After the successful completion of the course, the student will be able to:

·   Understand the basic questions in the field of modeling of biological processes, and to be able to make and implement corresponding models.

·     Understand the process of modeling through the stages of “inventing” the mathematical model, developing or using computational tools to solve the model, drawing conclusions based on the original model and finally the process of reviewing / expanding the model based on comparison with experimental observation.

·     Work in groups and individually to search for new concept.