AMBICON
Automated multi-level modeling of biological systems considering physico-chemical constraints
| Coordinatore | EBERHARD KARLS UNIVERSITAET TUEBINGEN
Organization address
address: GESCHWISTER-SCHOLL-PLATZ contact info |
| Nazionalità Coordinatore | Germany [DE] |
| Totale costo | 263˙448 € |
| EC contributo | 263˙448 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2012-IOF |
| Funding Scheme | MC-IOF |
| Anno di inizio | 2013 |
| Periodo (anno-mese-giorno) | 2013-07-01 - 2016-08-30 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
EBERHARD KARLS UNIVERSITAET TUEBINGEN
Organization address
address: GESCHWISTER-SCHOLL-PLATZ contact info |
DE (TUEBINGEN) | coordinator | 263˙448.60 |
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Obiettivo del progetto (Objective)
'The aim to make biological phenomena predictable is the driving force of research in systems biology. The ability to simulate entire cellular systems in the computer would be of great benefit for the biotechnological production of medication and the development of personalized medicine. To this end, the development of mathematical models plays a central role. The horizontal integration of models developed for gene regulation, signal transduction, or metabolism into a broader picture of the cellular interplay belongs to the most challenging problems of this endeavor: Models need to be combined that have solely been developed for one particular aspect. Only based on a holistic and detailed description of all cellular processes reliable computer models can be created by incorporating physico-chemical constraints that limit the model to experimental and real-world conditions. The creation of individual models is still not straightforward. Due to the complexity of the systems and the ability to simultaneously quantify several thousands of biological entities, this approach can only be feasible with the help of precise automated methods that reduce the human effort for model creation to a minimum. This project aims to unify the existing theoretical approaches for model creation (MASS and AMUSE). The effectiveness of these methods will be validated in an application to large-scale metabolic data (evolved E. coli, human erythrocytes and platelets). The combined wet-lab/dry-lab research facility at the University of California, San Diego, (UCSD) provides an excellent environment for the training of the applicant: Hands-on experimentation practice and effective large-scale study design involving biologists and modelers will be valuable learning objectives for the later establishment of independent research projects in Europe.'