Traditional molecular biology follows the reductionist paradigm of "one gene, one protein, one function". However, with the ever increasing amount of data generated through genome-scale experiments, it becomes clear that "the whole is more than the sum of the parts".
In this lecture, we introduce the exciting new field of computational systems biology, which attempts to integrates orthogonal data to understand biological systems as a whole. The lecture can be divided into three parts.
In part one, we overview the field and present the big picture and motivation. A primer of molecular biology is included to make sure that all course participants, especially those with purely computer science background, have the requisite vocabulary. To conclude, we show how traditional sequence analysis can play a role in systems biology.
Part two focuses on protein structure. While systems biology itself looks at the big picture, for a complete understanding one still has to go down to the individual building blocks. "Parts" and "whole" are really the two sides of the same coin. With the facility to freely navigate between the two, one will understand both at a deeper level.
Part three is "proper" network-based systems biology. The prime focus is protein-protein interaction networks, but others such as gene-regulatory and metabolic networks are also presented. While we provide the necessary theoretical background on networks, the focus is on addressing significant biological questions and conducting cutting-edge research. Finally, we introduce pathogen-host interactions as a first example of integrating multiple systems.
The course is aimed at Master students, but should be accessible to Bachelor students as well.