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CamOptimus

Self-contained user-friendly multi-parameter optimisation platform for non-specialist experimental biologists

The Idea

Biological problems are usually complex due to their multi-parametric nature and to the fact that these parameters are often interdependent. A commonly employed approach in attacking such problems relies on the use of background knowledge, or informed guesswork, to prioritise these parameters. For novel systems there may be insufficient background knowledge to enable successful prioritisation. Moreover, identifying and testing the effect of individual parameters is often an ineffective strategy because it ignores the interactive effects of mutually dependent parameters.

CamOptimus developed a hybrid approach to solve multi-parametric experimental design problems and to develop a simple-to-use and freely available graphical user interface (GUI) to empower a wider audience of experimental biologists to employ GA in solving their optimisation problems. 

 

The Team

Dr Duygu Dikicioglu
Dr Duygu Dikicioglu
Dr Ayca Cankorur-Cetinkaya
Dr Ayca Cankorur-Cetinkaya
Dr Joao ML Dias
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John Kendall

 

Dr Duygu Dikicioglu 

Post Doctoral Research Associate, Department of Biochemistry

Ayca Cankorur-Cetinkaya

Post-doctoral Research Associate, Department of Biochemistry

João ML Dias

Bioinformatician, Research Associate, Department of Haematology and Sanger Institute

John Kendall

Principal scientist, PhD, ZuvaSyntha Ltd

 

Project Outputs

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The Synthetic Biology Strategic Research Initiative provides a hub for anyone interested in Synthetic Biology at the University of Cambridge, including researchers, commercial partners and external collaborators. 

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