"Quantifying signal transduction" (QUASI) is an EC-funded project starting early in 2004. It deals with signalling through MAP kinase pathways, taking a systems biology approach.

It consists of the following groups:

  1. Göteborg University, Stefan Hohmann, Per Sunnerhagen, Markus Tamás, Morten Grötli
  2. Universitat Pompeu Fabra, Barcelona, Francesc Posas
  3. University of Vienna, Gustav Ammerer
  4. Eidgenössische Technische Hochschule Zürich, Matthias Peter
  5. Max-Planck Institut für Molekular Genetik, Edda Klipp
  6. Mälardalens Högskola, Rune Pettersson

This is the abstract of the project:

The present understanding of cellular signal transduction is restricted, at the best, to the wiring schemes of signalling pathways. Little is known about the details of their dynamic operation and the importance of quantitative, spatial and time-dependent parameters for signalling output. Those are, however, crucially important for drug discovery and application. QUASI is a multidisciplinary project with the goal to obtain a coherent and detailed picture of the dynamic operation of a model signalling transduction network. The signalling pathways contain the evolutionarily conserved MAP kinase cascade module, which is of central importance for signalling in human cells and implicated in human diseases such as cancer and inflammatory disorders. MAP kinase pathways are currently being explored as drug targets. A better understanding of the dynamic operation of these pathways offers new opportunities for drug discovery and for efficient individualised treatment based on the genetic setup of the patient (pharmacogenomics).

To achieve the goals of QUASI, quantitative data of high definition on signal transduction activation and deactivation will be obtained using frontline experimental approaches encompassing global gene expression, proteomics, bioimaging and chemical genetics. A software-implemented mathematical model of signalling dynamics will be constructed from pre-existing data and data generated within the consortium. Predictions from the model will be used as a basis for experimentation to further enhance the model, in a recursive manner. An interactive dynamic visual interface will be constructed to allow the experimenter to explore the effects of virtual manipulations of the system. This tool will enhance the intuitive understanding of intracellular signalling and this interface could be developed into a general tool for education as well as prediction of drug effects.

Recruitment is going on, contact the group leaders to ask for opportunities. There are two openings in Göteborg at the moment.