SYSTEAM
Systems and Signals Tools for Estimation and Analysis of Mathematical Models in Endocrinology and Neurology
| Coordinatore | UPPSALA UNIVERSITET
Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie. |
| Nazionalità Coordinatore | Sweden [SE] |
| Totale costo | 2˙378˙999 € |
| EC contributo | 2˙378˙999 € |
| Programma | FP7-IDEAS-ERC
Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | ERC-2009-AdG |
| Funding Scheme | ERC-AG |
| Anno di inizio | 2010 |
| Periodo (anno-mese-giorno) | 2010-04-01 - 2015-03-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
UPPSALA UNIVERSITET
Organization address
address: SANKT OLOFSGATAN 10 B contact info |
SE (UPPSALA) | hostInstitution | 2˙378˙999.50 |
| 2 |
UPPSALA UNIVERSITET
Organization address
address: SANKT OLOFSGATAN 10 B contact info |
SE (UPPSALA) | hostInstitution | 2˙378˙999.50 |
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Obiettivo del progetto (Objective)
'This proposal envisages a research program in the field of systems and signals that will lead to innovative and agile mathematical modeling as well as model-based signal processing and control tools for applications in biology and medicine. The project's goal is to bridge the gap between systems biology, on one hand, and medical signal processing and control engineering, on the other. Mathematical models of systems biology will be used to devise algorithms for biological data processing and computerized medical interventions. Experimental biological and clinical data will be utilized to estimate and characterize the parameters of mathematical models derived for biological phenomena and mechanisms. An extensive collaboration network of medical researchers from Sweden and abroad will provide the project team with necessary experimental data as well as with access to medical competence. The envisaged tools are expected to be applicable more generally but their efficacy will be demonstrated in two main application areas. These areas are endocrinology and neurology for which the use of formal control engineering and signal processing methods is currently deemed to be most promising. The proposed program will result in novel systems and signals tools for medical research and health care enabling multi-input multi-output modeling and analysis of endocrine regulations and providing model-based algorithms for individualized drug dose titration.'
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