| EPSRC Reference: |
EP/H027955/1 |
| Title: |
Towards Industrial Applications of Modular Languages for Biology |
| Principal Investigator: |
Pedersen, Dr MD |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
School of Biological Sciences |
| Organisation: |
University of Cambridge |
| Scheme: |
Postdoc Research Fellowship |
| Starts: |
01 September 2010 |
Ends: |
31 August 2013 |
Value (£): |
250,340
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| EPSRC Research Topic Classifications: |
| Fundamentals of Computing |
Synthetic biology |
| Theoretical biology |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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27 Jan 2010
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PDRF CDIP Interview Panel
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Announced
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17 Dec 2009
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PDRF CDIP Sift Panel
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Excluded
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Summary on Grant Application Form |
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Systems biology is a relatively new field which seeks a systems level understanding of organisms: rather than studying individual entities such as proteins and genes in isolation, we ask how these interact in order to form the complex emerging behaviour that living systems exhibit. Such an understanding is for example important for the development of new drugs and to predict how these impact on an organism. Synthetic biology is a related and emerging field which seeks to engineer new organisms for practical purposes. Examples include bacteria that produce energy from sunlight; cells which organise to form e.g. artificial human tissue; and crops which are resistant to bugs. Both systems and synthetic biology rely on mathematical models. In systems biology, models are used to formalise our knowledge about an existing biological system and to allow computer simulations which predict its behaviour. In synthetic biology a model similarly allows us to test the behaviour of a new system before it is implemented in the lab. As we gain more biological knowledge and models become larger, more structured modelling methods are also needed. Computer science has a rich history in inventing and applying formal languages which support modelling in engineering, and over the last decade, substantial research efforts have gone into creating such formal languages for biology. However, these languages have so far been applied mainly to small-scale, proof-of-concept examples that yield little or no biological insight. In particular, formal languages have not yet gained traction in industry. The vision of the proposed project is to change this situation. I propose to do so by taking two existing languages that have been the subject of my PhD, one for systems biology and one for synthetic biology, and targeting the development of these languages towards industrial applications. The languages are good starting points for this purpose because they have already been designed with three key features in mind: 1) they are modular, so large systems can be described systematically in terms of their components; 2) they are intuitive to use and can be understood by non-specialists; and 3) they are defined mathematically and can hence be read by computers. The synthetic biology language furthermore allows the translation of a model to DNA sequences that can be put to work in living cells.To achieve the aim of industrial applicability in systems biology, I propose to work closely with industry. In particular, I will work with Novo Nordisk/HRI on the development of a model of insulin signalling used in their diabetes research, and through this I will obtain valuable insight into the requirements for a modelling language. I will also work and exchange ideas with Plectix BioSystems, which is developing another formal language that complements the languages in this proposal. For synthetic biology, an attempt to bring a dedicated formal language to industry would be premature given that the field is currently in its infancy. Instead, my aim is here to develop a language which can be of practical use in the annual international Genetically Engineered Machines (iGEM) competition projects. The projects are carried out by undergraduate teams from over 20 different countries and lie at the cutting edge of synthetic biology. This proposed work will involve the design of a new database of genetic parts that is necessary for the translation to DNA, and on the biological side this database will be developed at Cambridge University. The work will also focus on efficient methods of translation to DNA since the existing methods do not scale to real applications; and finally the work will study new ways of describing cell-cell communication and the impact of a synthetic circuit on host cells. This will be done in collaboration with Microsoft Research.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
http://mdpedersen.azurewebsites.net |
| Further Information: |
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| Organisation Website: |
http://www.cam.ac.uk |