Systematic Models for Biological Systems Engineering Training Network
Description: Mathematical, computational models are central in biomedical and biological systems engineering; models enable (i) mechanistically justifying experimental results via current knowledge and (ii) generating new testable hypotheses or novel intervention methods.
SyMBioSys is a joint academic/industrial training initiative supporting the convergence of engineering, biological and computational sciences. The consortium's mutual goal is developing a new generation of innovative and entrepreneurial early-stage researchers (ESRs) to develop and exploit cutting-edge dynamic (kinetic) mathematical models for biomedical and biotechnological applications. SyMBioSys integrates: (i) six academic beneficiaries with a strong record in biomedical and biological systems engineering research, these include four universities and two research centres; (ii) four industrial beneficiaries including key players in developing simulation software for process systems engineering, metabolic engineering and industrial biotechnology; (iii) three partner organisations from pharmaceutical, biotechnological and entrepreneurial sectors. SyMBioSys is committed to supporting the establishment of a Biological Systems Engineering research community by stimulating programme coordination via joint activities.
The main objectives of this initiative are:
* Developing new algorithms and methods for reverse engineering and identifying dynamic models of biosystems and bioprocesses
* Developing new model-based optimization algorithms for exploiting dynamic models of biological systems (e.g. predicting behavior in biological networks, identifying design principles and selecting optimal treatment intervention)
* Developing software tools, implementing the preceding novel algorithms, using state-of-the-art software engineering practices to ensure usability in biological systems engineering research and practice
* Applying the new algorithms and software tools to biomedical and biological test cases.
Funder: European Commission
Amount: €3,805,000
Funding type: fellowship
Funder scheme: H2020 - MSCA-ITN-ETN
Start date: 2015-09-01
End date: 2019-08-31
Institution: IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE
Funded outputs count: 37
Funder award ID: 675585
OpenAlex ID: G3585592020