Molecular Epidemiological studies, and evaluation of these, are becoming increasingly important both in academia and industry. Molecular epidemiology is for example an important tool in the development of personalized medicine. With focus on different biological measurement approaches and epidemiological study designs, this course describes how molecular and epidemiological methods can be used to understand biological processes and infer disease mechanisms. The course also describes how molecular epidemiology can be used to identify new biomarkers and evaluate their clinical usefulness. 'Omics' technologies (i.e. genomics, epigenetics, proteomics, metabolomics) and statistical analytical approaches will be extensively covered
The course will highlight advantages and disadvantages with different epidemiological study designs ranging from cross-sectional, cohort, and case-control to family-based designs. Statistics on the course will cover basic measurements and approaches for hypothesis testing, such as t-test, multivariate regression, and risk prediction models.
The course will include mandatory computer labs and group discussions (e.g. regarding ethical considerations surrounding use of human samples and sensitive data form individual subjects) as well as a mandatory group project.
