Networks in the Life Sciences – Genomics, Proteomics and Systems Biology
14th EMBL PhD Symposium

25th–27th October 2012

Speaker: Prof. Dr. Dr. Dagmar Iber

  • Swiss Institute of Bioinformatics, Basel
  • ETH Zürich Department of Biosystems Science and Engineering

Background

Dagmar Iber A doctor in both biochemistry and mathematics, Dagmar Iber leads a group at ETH Zürich. She studies cellular signaling networks, especially those involved in developmental cell fate determination. By developing quantitative & predictive models her group aims to contribute to an understanding of how these networks evolve.

Talk: From Networks to Medical Applications – Computational Models of Development

Mouse organogenesis has been studied for decades. While much is known about the genes that affect organ formation, general regulatory paradigms are largely lacking to explain the emergence of functional organization in biology. A number of mathematical theories have been proposed to explain biological pattern formation, but these have rarely been validated experimentally. With the emergence of the field of systems biology the two approaches are becoming increasingly interlinked. This has allowed the generation of experimentally validated computational models of mouse organogenesis integrating detailed experimental knowledge.

I will present our recent models of lung and kidney branching morphogenesis, for limb and bone development, as well as for ovarian follicle development. Our data-based models not only help to detect inconsistencies in experimental data, but also allow to define the underlying regulatory mechanisms and to distinguish core and accessory regulatory interactions. These models also present a useful tool for in silico genetics, i.e. the computational simulations of the expected phenotypes of mutant states that are difficult or impossible to generate by mouse molecular genetics. Finally we seek to use our mechanistic insights in the engineering of bone from mesenchymal stem cells and in defining the molecular causes of infertility.