Research group Erik van Nimwegen

Unraveling the functioning and evolution of genome-wide regulatory networks

Using theoretical and experimental approaches to study the function and evolution of the regulatory networks that cells use to control the expression of their genes.

The computationally reconstructed core transcription regulatory network that controls differentiating human THP-1 cells.

Given the enormous variety of animal cells across different tissues and organs, it is easy to forget that all cells of an organism share a common "blueprint", i.e. a common genome. We now know that the major determinant of a cell's state is the expression pattern of its genes which is controlled by regulatory genes. They bind to short sequence patterns in the DNA and, in this way, "read out" the regulatory programs encoded in the genome.

Deciphering the regulatory code of the genome

In contrast to the large genes that encode proteins, the small regulatory sequences that control gene expression are generally hard to find. Moreover, little is known about their functioning. Our group develops mathematical and computational methods for deciphering this "regulatory code" in the DNA, and for modeling how constellations of regulatory sequences control gene expression.

Modeling gene expression dynamics

Recently developed experimental technologies make it possible to comprehensively monitor the internal states of cells. We integrate computational predictions with such experimental data-sets to model the dynamics of gene regulation in organisms from E. coli to human. Our ultimate goal is to learn how to actively manipulate the regulatory networks that control cellular behavior. Such ability has potential applications ranging from "domesticating" pathogenic organisms to engineering human tissues.

Discovering the laws of genome evolution

Little is known about the selective forces that drive genome evolution in nature. With the advent of large-scale genome sequencing it has become possible to empirically study quantitative patterns of genome evolution. Our group works on identifying universal quantitative laws in genome evolution, and understanding the origins of these laws.