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Biomedical Mathematics - Period 1+2
OVERVIEW
CEA CAPA Partner Institution: Vrije Universiteit Amsterdam
Location: Amsterdam, Netherlands
Primary Subject Area: Mathematics
Instruction in: English
Course Code: X_401056
Transcript Source: Partner Institution
Course Details: Level 300
Recommended Semester Credits: 3
Contact Hours: 84
DESCRIPTION
This course consists of two parts.
The first parts has two sections. In both sections processes in the cell are modelled. An event in a cell does not occur in isolation, but occurs in relation to the rest of the cell. In the entire course these dependencies are modelled. Wherever possible examples from the VUmc medical hospotical are used to illustrate statistical techniques. In the first section of this part we focus on modelling DNA sequences. The resulting models are used to describe the evolution of cancer cells. Using hidden Markov chain models the exon-intron structure of a gene is studied. We also describe the evolution of DNA to reconstruct phylogenetic trees (trees of descent). In the second section, we try to unravel the topological structure of gene regulatory networks on the basis of gene expression data. Can we uncover which genes works together?
In the second part of the course, we will cover deterministic models of biological processes, both using discrete and continuous time models. We will treat how to set up equations, analyse the resulting model and how to interpret the results back into the biological context. We will cover various biological and biomedical applications, such as ecology, epidemiology and chemical reactions.
Vrije Universiteit Amsterdam (VU Amsterdam) awards credits based on the ECTS system. Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.
The first parts has two sections. In both sections processes in the cell are modelled. An event in a cell does not occur in isolation, but occurs in relation to the rest of the cell. In the entire course these dependencies are modelled. Wherever possible examples from the VUmc medical hospotical are used to illustrate statistical techniques. In the first section of this part we focus on modelling DNA sequences. The resulting models are used to describe the evolution of cancer cells. Using hidden Markov chain models the exon-intron structure of a gene is studied. We also describe the evolution of DNA to reconstruct phylogenetic trees (trees of descent). In the second section, we try to unravel the topological structure of gene regulatory networks on the basis of gene expression data. Can we uncover which genes works together?
In the second part of the course, we will cover deterministic models of biological processes, both using discrete and continuous time models. We will treat how to set up equations, analyse the resulting model and how to interpret the results back into the biological context. We will cover various biological and biomedical applications, such as ecology, epidemiology and chemical reactions.
Vrije Universiteit Amsterdam (VU Amsterdam) awards credits based on the ECTS system. Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.
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