SMTK20001U Advanced Physiological Modelling
MSc Programme of Biomedical Engineering - Restricted elective in the Technological Specialization
MSc Quantitative Biology and Disease Modelling - Restricted elective in the Technological Specialization
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 techniques and computational algorithms. A wide variety of topics are touched upon: from cellular signaling and biological rhythms to neuronal and vascular networks.
After participating in the course, the student must demonstrate the following abilities at a sufficient level:
Knowledge
Understand mathematical/physics concepts (dynamical systems, oscillation theory, network theory, synchronization theory, statistics, survival analysis)
Understand computational algorithms behind Matlab/Python/R scripts related to biosimulations
Explain topology 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
Review scientific literature on physiological modeling and related data analysis, critically assess the use of methods and obtained results
Assess complex networks of the human body by treating a sequence problems at the intracellular, intercellular, whole organ and systemic levels
Perform theoretical and computational analysis of dynamical patterns of physiological models and reveal parameters responsible for pathological conditions
Optimize/develop computation algorithms to perform biosimulations
Convey a physiological problem solving into a report and a Power Point presentation
Competence
To formulate mechanism-based and data-driven 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
- Lectures
- 24
- Preparation
- 226
- Project work
- 24
- Exam
- 0,5
- Total
- 274,5
Course registration takes place at DTU
Open for credit transfer students and other external students.
Apply here:
Credit transfer students:
Credit transfer student at SUND – University of Copenhagen
(ku.dk)
Other external students:
https://healthsciences.ku.dk/education/student-mobility/guest-students/
- Credit
- 2,5 ECTS
- Type of assessment
- Course participation
- Type of assessment details
- Participation in all written and oral assignments through the course and approval of the final written report
- Aid
- All aids allowed
- Marking scale
- passed/not passed
- Censorship form
- No external censorship
Criteria for exam assesment
To obtain the course certificate the student must be able to
Knowledge
- Understand underlying mathematical/physics concepts
- Understand advanced computational algorithms used for modeling
- Explain biological background of the model
- Understand regulatory mechanisms of biological rhythms/networks and their mathematical models
Skills
- Discuss modeling approaches depending on the purpose of study
- Reproduce, modify and simulate models from scientific literature
- Discuss reproducibility and comparability of relevant computational models
- Apply mathematical/physical concept to particular biomedical problem
- Formulate a model and discuss its possible simplifications/extension and dynamics
- Develop algorithms to perform simulations
- Improve scientific writings in English language
- Credit
- 7,5 ECTS
- Type of assessment
- Written assignmentOral examination, 30 min.
- Type of assessment details
- Oral exam includes a presentation of the project on the basis of the written report and discussion of biological, mathematical, and computational aspects of the project.
- Exam registration requirements
Achieved course attestation (SMTK20001E) 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
One internal examiner
Criteria for exam assesment
In order to obtain the grade 12, the student must demonstrate the following abilities at a sufficient level:
Knowledge
- Explain physiology and regulatory mechanisms related to normal and pathological conditions
- Understand mathematical/physics concepts underlying modeling approach
- Understand computational algorithms behind scripts related to biosimulations
- Understand assumptions and simplifications needed to build a reliable model
- Understand dynamical/statistical features of the model and their relevance to certain pathological conditions
Skills
- Review of scientific literature on physiological modeling and related data analysis, critically assess the use of methods and obtained results
- Discuss reproducibility and comparability of relevant computational models and approaches
- Perform theoretical and computational analysis of dynamical patterns of physiological models and reveal parameters responsible for pathological conditions
- Optimize/develop computation algorithms to perform biosimulations
- Convey results into a scientifically written report and a Power Point presentation
Course information
- Language
- English
- Course code
- SMTK20001U
- Credit
- See exam description
- Level
- Full Degree Master
- Duration
- 1 semester
- Placement
- Autumn
- Schedule
- See Syllabus
- Course capacity
- 60 participants
Study board
- Study board from DTU
Contracting department
- Department of Biomedical Sciences
Contracting faculty
- Faculty of Health and Medical Sciences
Course Coordinators
- Olga Sosnovtseva (4-73706b654477797268326f7932686f)
Questions about teaching or team setting for your KU-courses, please contact: Undervisning@sund.ku.dk
Questions about exams for your KU-courses, please contact:
eksamen@sund.ku.dk
Questions about study planning for your KU courses, please contact:
vejledning@sund.ku.dk