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Bork Group

Deciphering function and evolution of biological systems

Mycoplasma pneumonia. Together with other SCB groups, we overlay genomic, transcriptomic, proteomic, metabolic and structural data to establish a model organism for systems biology and discover lots of exciting biology on the way (see Kuehner et al., 2009, Guell et al., 2009 and Yus et al., 2009, all Science). The figure depicts a tomographic snapshot, a single particle EM of the ribosome (many proteins of which have unexpected links to various cellular processes indicated by lconnectors) and a metabolic reconstruction in which the correspondence to operon organisation is shown (blue). 

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Integration of metagenomics data with environmental factors. Using novel visualization concepts and statistical approaches we can correlate the abundance of molecular functions to external data (e.g. Gianoulis et al., 2009, PNAS; Qin et al., 2010, Nature). For example, many distant ocean samples are analysed and the abundance of some pathways significantly correlate with temperature or oxygen concentration of both. In human, we find correlations of gut genes from metagenomes with several diseases. 

Previous and current research

The main focus of our computational biology group is to gain insights into biological systems and their evolution by comparative analysis and integration of complex molecular data. The group currently works on three different spatial scales, but with common underlying methodological frameworks:

  • genes, proteins and small molecules;
  • networks and cellular processes;
  • phenotypes and environments, often related to diseases.

We are aiming at biological discoveries and often develop tools and resources to make this happen.We usually work in new or emerging areas of biology; for example we have projects that integrate drugs (and other small molecules) with cellular and phenotypic information to predict new uses for old drugs (e.g. Campillos et al., 2008, Science) or find biomolecules that cause disease or side effects.We study temporal and spatial aspect of protein networks to identify biological principles that determine function and evolution (e.g. de Lichtenberg et al., 2005, Science; Jensen et al., 2006, Nature; Kuehner et al., 2009, Nature). We also trace the evolution of the animal gene repertoire (e.g. Ciccarelli et al., 2006, Science) and, for example, connect gene losses and duplications with morphological or life style changes. We study environmental aspects via comparative metagenomics (Tringe et al., 2005, Science; von Mering et al., 2007, Science; Qin et al., 2010, Nature) and hope to find marker genes for various diseases like obesity but also to understand microbial community interactions. All our projects are geared towards the bridging of genotype and phenotype through a better understanding of molecular and cellular processes.

The group is partially associated with the Max Delbrück Center for Molecular Medicine in Berlin and with the Molecular Medicine Partnership Unit at Heidelberg University.