Biological systems are complex systems composed of many spatially distributed building blocks. Understanding the evolution, dynamics and emergent behavior of complex biological systems requires a systems biology approach, involving quantitative biology, mathematical modelling, computer simulation and bioinformatics.
Rob J. de Boer
The immune system is a fascinating complex system taking decisions on how to respond to a wide variety of stimuli. I am an immunologist using mathematical models, computer simulations, and bioinformatics to understand the functioning of the immune system in a quantitative manner.
Vertebrate cells present short peptides from internal proteins to signal to the immune system. I develop and apply bioinformatic methods to identify antigenic peptides in the proteome of pathogens, tumors, and hosts, and study how these peptides signal to the immune system.
I develop multi-scale computational models to unravel pattern formation during development. I focus on the growth and patterning of the major body axis in animals and plants. A major aim is to find general evolutionary and developmental design principles.
We study the immune systems of primates and their co-evolution with pathogens by a comparative genetics approach, focussing on the genes of the Major Histocompatibility Complex (MHC) and Killer Cell Immunoglobulin-like receptors (KIR). The MHC is associated with susceptibility and resistance to a myriad of diseases.
I study biological evolution in heterogeneous environments using theoretical (mathematical) models, and aim to understand the growth of bacteria on mixed-substrate media based on coarse-grained, systems-level constraints and principles.