At the end of the course, students should:|
i) Understand the role of bioinformatics and computational biology in modern biology.
ii) Understand the basic principles of bioinformatics and computational biology approaches.
iii) Have obtained knowledge of the power and the caveats of these approaches.
iv) Be able to propose appropriate systems biology approaches to answer research questions
At the end of the course, students should be able to:
i) Discuss and critically assess literature from this field of research at academic level
ii) Place this field of research in context of other research themes to promote interdisciplinary thinking
iii) Place this field of research into the larger societal context.
Systems biology aims to approach biological research questions in an integrative, interdisciplinary and quantitative manner to help provide a mechanistic understanding of biological processes.
In this course you will learn how many complex biological phenomena can not be understood from a reductionist approach focusing on a single gene, protein or celltype but that instead the networks of interactions amongst many different involved factors need to be taken into consideration. You will learn how high-throughput experiments combined with bioinformatic data-analysis enable us to map out these networks as well as how computational modeling allows us to improve our understanding of the functioning of these networks. Students will learn the basic principles behind these bioinformatic and computational biology approaches, their strengths and weaknesses, and when these can be applied. The application of these approaches to a wide range of biological research questions will be illustrated by experts in the field.
Similar to other general track courses of the MCLS master, each day of
the course is focused on a specific topic and may include lectures by principle investigators, research seminars, or guest lectures. In addition students are expected to discuss and present research papers.