SMTK12022U Advanced Physiological Modelling
The course aims to provide overview of current research topics in mathematical physiology by synthesizing a coherent description of the physiological background with realistic mathematical models and their analysis. The program will give students the opportunity to develop mathematical and computer modeling skills, whilst at the same time will introduce students to cutting-edge experimental and computational techniques. A wide variety of topics are touched upon, from biochemistry and cellular signaling to neural activity and vascular networks.
Knowledge
Understand mathematical/physics concepts (stability analysis, oscillation theory, synchronization theory, reaction-diffusion equations)
Understand computational algorithms behind Matlab scripts related to biosimulations
Explain morphology and dynamics of biological networks and their relevance to normal and pathological conditions
Understand what assumptions and simplifications are needed to build a model
Understand underlying signaling mechanisms and corresponding control parameters in a model related to a certain disease
Skills
Analyze a scientific article on physiological modeling and related time-series analysis, critically assess the use of methods and published results
Analyze complex networks of the human body by treating in sequence problems at the intracellular, intercellular, whole organ and systemic levels
Perform theoretical and computational analysis of dynamical patterns in biological networks and reveal parameters responsible for pathological conditions
Convey a physiological dynamical problem into a report and a power point presentation
Competence
To formulate mechanism-based models and choose appropriate computational methods to investigate them
To interpret dynamical features of the biomedical systems in term of biology and mathematics
To integrate fundamental knowledge from physics, mathematics and biology to provide better understanding of regulatory mechanisms at different levels of organization
Lecture notes and scientific papers
- Category
- Hours
- Exam
- 1
- Lectures
- 24
- Preparation
- 155
- Project work
- 80
- Total
- 260
- Credit
- 10 ECTS
- Type of assessment
- Written assignmentOral examinationOral exam including a presentation of a project assignment and written critique of a project assignment prepared by others.
- Exam registration requirements
- Achieved course attestation in Course in Advanced Physiological Modelling by handing-in of project assignment and assessment/criticism of received assignment.
- Aid
- Without aids
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
More than one internal examiner
Criteria for exam assesment
Knowledge
Understand mathematical/physics concepts (stability analysis, oscillation theory, synchronization theory, reaction-diffusion equations)
Understand computational algorithms behind Matlab scripts related to biosimulations
Explain morphology and dynamics of biological networks and their relevance to normal and pathological conditions
Understand what assumptions and simplifications are needed to build a model
Understand underlying signaling mechanisms and corresponding control parameters in a model related to a certain disease
Skills
Analyze a scientific article on physiological modeling and related time-series analysis, critically assess the use of methods and published results
Analyze complex networks of the human body by treating in sequence problems at the intracellular, intercellular, whole organ and systemic levels
Perform theoretical and computational analysis of dynamical patterns in biological networks and reveal parameters responsible for pathological conditions
Convey a physiological dynamical problem into a report and a power point presentation
Course information
- Language
- English
- Course code
- SMTK12022U
- Credit
- 10 ECTS
- Level
- Full Degree Master
- Duration
- 1 semester
- Placement
- Spring
- Schedule
- See Syllabus
- Course capacity
- 60 participants
- Study board
- DTU Elektro
Contracting department
- Department of Biomedical Sciences
Course responsibles
- Olga Sosnovtseva (olga@sund.ku.dk)