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Project 1: Phenotypic assesment of fine motor, cognitive and emotional disturbances in a transgenic rat model for SCA 17 and use of identified read-outs in a gene therapy study

PI:Hoa Nguyen, Eberhard Karls University of Tuebingen

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Project 3: New technology for tracking and analysis of rat social behaviour

PI: Lucas Noldus, Noldus Information Technology

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PhenoRat is an international and intersectoral PhD programme for highly motivated young scientists, where state-of-the-art research is combined with a comprehensive training programme.

The scientific goal of PhenoRat is to generate, characterise and validate transgenic rat models of two neurodegenerative diseases: Huntington disease (HD) and spinocerebellar ataxia type 17 (SCA17). Besides traditional methods of analysis of behavioural data, new statistical methods will be developed to enable behavioural classification of transgenic and wild type animals. This will enable the detection of early onset of specific symptoms and provide read-out parameters in pre-clinical studies applying novel substances for the treatment of HD and SCA17. Last but not least these read-outs will be validated in a gene therapy study with SCA17 rats using Antisense Oligonucleotides (AONs) against the PolyQ stretch of TBP.

European Industrial Doctorates have the objective to train highly-skilled researchers and to stimulate entrepreneurship, creativity and innovation in Europe. This will be achieved by involving business in doctoral training so that skills better match public and private sector needs. We have assembled a unique consortium in which industry (Noldus Information Technology and Delta Phenomics, both Netherlands), academia (University of Tuebingen, Germany), and a university-related foundation for entrepreneurship (StartLife, Netherlands) will work closely together to achieve both organization of an excellent training program and performance of excellent research projects with a pronounced focus on inter-sectoral doctoral education and transfer of knowledge.

PhenoRat is funded from the European Community‘s Seventh Framework Programme FP7/2012 under grant agreement No. 317259
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