Developing single cell technologies for systems biology
Description: "Biological cells are entities with highly complex, non-linear control circuits. They can thus express intricate behavior, such as stochasticity-induced multistability, oscillations, responses at different time scales, hysteretic behavior, memory, etc. Biology is only about to start to investigate these phenomena, which all occur at single cell level and often result in phenotypic heterogeneity. It is required to experimentally probe single cells, as population-level analyses will mask most of the behaviors of individual cells. Development of single cell measurement techniques represents an area for exciting research and development, being the key enabling technique to ultimately understand important complex biological behaviors. The education of highly qualified specialists with multidisciplinary skills is a pivotal prerequisite for addressing these biological problems and, even more importantly, for transferring this knowledge into marketable products.
This proposal seeks funding for a truly interdisciplinary European consortium to train researchers to develop and exploit novel technologies for single-cell analysis in the context of system-level metabolic cell behavior. The crucial importance of single cell analysis has been stressed in a recent Science News Focus and the area of metabolism was highlighted in Nature’s “New year, new science"" outlook for 2011.
ISOLATE represents an Initial Training Network involving eleven trainees. A range of methodologies will be included to provide unique training to fellows in single cell analyses and to investigate complex phenomena. A high degree of multidisciplinarity and the inclusion of key industrial stakeholders make ISOLATE especially suitable for a training program ranging from forefront microtechnology, bioengineering, biophysics, via analytical chemistry to biochemistry and systems biology."
Funder: European Commission
Amount: €2,995,000
Funding type: training
Funder scheme: FP7 - MC-ITN
Start date: 2012-01-01
End date: 2015-12-31
Institution: GOETEBORGS UNIVERSITET
Funded outputs count: 19
Funder award ID: 289995
OpenAlex ID: G7300720356