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Molecular Data Science: from disease mechanisms to personalized medicine
Focus of the course: Molecular Epidemiology in Ageing research
Biomedical research increasingly involves the generation and analysis of very large data sets whether it is whole-genome DNA sequencing, gene expression, or magnetic resonance imaging data. In particular, large-scale data will be the cornerstone of personalized medicine. This course is aimed at biomedical students who not only want to be responsible for the generation of large-scale data in their future projects, but also want to be able to analyse and interpret their own data.
Literature and documents for study assignments will be handed out during the course.
Coordinators
Bas Heijmans, Molecular Epidemiology; 071-526 69785, [email protected]
Ingrid Meulenbelt, Molecular Epidemiology; 071-526 9734, [email protected]
Location
Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden: Room J1-84 at the main building.
For the practicals, computers in J1-84 will be used.
Storing valuables
Store valuables, especially during breaks, in one of
the lockers available for library users, located on the left of the
library entrance.
Assessment plan
Handing in assignments (Pass/Fail, individually assessed).
Contribute to interim evaluation of student participation and development during workgroups (0%).
Fill out project proposal form as preparation for reflective assignment (0%).
Presentation project proposal (background, hypothesis, pilot data, objectives, study design, workplan, expected outcomes; 45%, assessed in duos).
Active and critical participation during discussion after project presentations of peers (15%, individually assessed).
Reflective assignment that shows mastering key aspects of development of research proposal in molecular data science and addressing points raised during peer review (40%, individually assessed).
Overall the evaluation will be a score between 0-10 composed of a weighted average of the different modules.
Part 1: Acquiring Knowledge and Skills
Students will gain knowledge of the different study designs used in investigations, with a focus on complex diseases. In the practicals, students will acquire skills (bioinformatic and statistical tools) that will enable them to analyse large datasets of genetic, gene expression, and phenotypic data, to identify patterns in this data, and match results with existing biological information to form new hypotheses.
Week 1
Monday October 21 (Location J1-84/building 1, LUMC)
Part 2: Applying Acquired Knowledge and Skills to Ageing.
Students will apply newly acquired skills to write a research proposal that follows a data science approach. This proporal will focus on ageing as a key example of a complex human trait. Students will work on developing a project proposal in pairs. Generating pilot data to support hypotheses by analyzing available real -omics data sets will be an integral part of the project proposal. During the week, there will be regular moments of interaction with the module coordinators and the opportunity to contact other tutors of the course.
Thursday November 7 (Location J1-84/building 1, LUMC)