PGCert Systems Biology
Postgraduate Certificate in Systems Biology
Fully online - distance learning
Systems biology is a rapidly emerging discipline within the life sciences, offering an organicist view on biology. It is making us aware of the connectedness of living systems where interactions between molecules, genes, cells, species and the environment are responsible for the regulation of biological functions. Systems biology aims to understand complex biological phenomena as integrated functioning systems. This level of understanding is facilitated by the quantitative analysis and modeling of the interactions among multiple components of a biological system. This approach involves concepts and tools from mathematics, statistics and computer science which conventional life science curricula do normally not cover in depth. The aim of the Postgraduate Certificate in Systems Biology is to equip you with knowledge from these areas, allowing you to explore and understand biology from a systems perspective. The course is aimed at students, researchers and practitioners with a life science background and emphasizes a conceptual and applied understanding of the relevant methods and tools.
Systems biology spans several disciplines and is by and large a team effort. Closing the communication gap between life science graduates and members of the other sciences (e.g. chemistry, physics, mathematics) and engineers (e.g. computer science) is therefore a particular challenge for a systems biology course. We have addressed this challenge by offering students a flexible, fully online course that makes use of modern teaching technologies guiding students through the interesting and challenging teaching material at their own pace.
This course is specifically tailored for biosciences graduates (as opposed to engineers, physicists or mathematicians) to embrace “systems thinking” and employ tools to tackle systems modeling and analysis tasks. Central to the approach taken in this course is to understand and apply fundamental concepts to problems, not on intricate technical details of mathematics and technology. This will enable students to speak a common language with system modelers and analysts, and to tackle more advanced topics in systems biology. The course relies on a single computing tool: the statistical and scientific programming language R. R is a open-source community effort and offers a huge arsenal of powerful functions to address a wide range of analytical and modeling problems. The R language and R software tools have gained an enormous popularity in the biological sciences over the last ten years. These tools and comprehensive documentation are freely available.