Mondrian Piet: Red Tree Erik van Nimwegen Group
Bioinformatics and Systems Biology


  1. General Research Interests

    The main research interests of the genome systems biology group center around the discovery and study of design principles in the control and regulatory mechanisms of cells. Among the natural sciences biology occupies a unique position in that it generally makes sense to ask not only how the system behaves and what its components are, but also why the system behaves the way it does. That is, since the biological systems that we find in nature are the result of an evolutionary process that took hundreds of millions of years, we expect that their behaviors are generally functional in the sense that they serve some purpose for the organism. However, there is as of yet no general theoretical framework for discerning 'function' in biological systems. In the last few decades molecular biology, and in particular high-throughput techniques, have lead to an explosion of our knowledge of the molecular components that make up biological systems, and their physico-chemical properties. Given such detailed knowledge of the microscopic components, standard simulation and analysis techniques can be used to investigate how the system will behave under various conditions. However, the question of why biological systems are designed the way they are has been left largely untouched. Our long-term goal is to develop a mathematical theory of function in biological regulatory networks. Such a theory would provide a general frame work to approach questions such as: How does one separate the accidental from the functional in biological systems? What is the 'purpose' of a particular biological network for the organism? Which features of its design contribute to this purpose and which are only there by historical accident?

    Recognizing that all 'function' in biological systems has arisen through evolution, one important aspect of the development of such a theory is the study of the evolutionary process. In particular we are studying evolutionary processes to understand how they have shaped regulatory design. A second line of investigation in our group concerns the direct study of large biological data sets. This part of our research consists mainly of the development of new mathematical techniques based on probability theory for interpreting large biological data sets. Finally, these two approaches are combined in our third current line of investigation which concerns the development of mathematical models for the evolution of whole genomes. Here we aim to explain quantitative laws of genome organization that are observed from large scale comparative genomics of whole genomes, and come to an quantitative understanding of the processes that shape whole genome evolution.

  2. Algorithms for unraveling the regulatory circuitry of cells

    The aim of these methods is to eventually produce highly reliable annotations of the regulatory signals in intergenic regions on a genome-wide scale to complement the annotation of protein coding regions that are currently available. We have been developing algorithms for the reconstruction of the genome-wide transcriptional regulatory networks using comparison of whole genomes. More recently we have also started developing methods that allow the incorporation of other types of data, such as microarray expression data and ChIP-on-chip data, into the comparative genomic analysis.

  3. Quantitative Laws in Genome Organization and Evolution

    With the recent exponential growth of the number of fully-sequenced genomes, meaningful quantitative comparisons of the content and structure of whole genomes have now become possible. These studies have uncovered basic quantitative laws that govern the gene-content of genomes, the distribution of genes within genomes, and the distribution of their interactions. We are studying these fundamental design principles in various ways. On the one hand we aim to discover further quantitative laws of genome design by the statistical analysis of large sets of genome sequence data. On the other hand we are developing mathematical models of whole genome evolution with the aim of elucidating the evolutionary origins of these genomic design principles.

  4. Microevolutionary Dynamics in Sequence Space

    Finally, our group also works on the general theory of micro-evolutionary dynamics of DNA sequences as a function of parameters such as population sizes, mutation rates, and structural features of the genotype to phenotype mapping. We are interested in the role of neutrality in evolution, the evolution of robustness to genetic and environmental perturbations, the evolution of regulatory circuitry, and the evolution of intergenic DNA.