• Registration is now open for our online conference

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  • Bootcamp 3 KUL

    Our 3rd bootcamp takes place in June ...

  • School 2 Paris

    Winter school at Institute Pasteur ...

  • School 3 Syros

    Completion of another successful School ...

  • TranSYS Journal Club report

    The TranSYS ITN holds a monthly journal club, organised by the TranSYS research council for its 15 ESRs. Each month a scientific paper is selected by majority from a list of three interesting papers and an ESR presents f...

  • Training

    The TranSYS training programme is designed to address critical skills gaps that are currently a bottleneck to advancing Precision Medicine. ...

  • The network

    Bringing together world leading experts in Preclinical Science & Molecular Diagnostics, Systems Analytics, and Targeted Therapeutics from industry and academia. ...

TranSYS is built around training 15 ESRs towards highly skilled jobs in the new area of Systems Health, while developing tools and approaches to exploit large and complex datasets, to advance Precision (Personalised) Medicine in several disease areas. TranSYS’s training programme and experience of different international research environments cuts across traditional data and life sciences silos. The emphasis on translational research will support new collaborations between academics and the pharma and health analytics sectors. Our ESR projects will advance the state of the art on biomarker discovery, improve understanding of disease-specific molecular mechanisms and target identification for optimal diagnostics, disease risk and treatment management, refine data generation and their management (including warehousing, disease-specific and standardised approaches for data processing, visualisation and model development) leading to improved clinical study design, clinical sampling and more targeted therapeutics. This ETN will internationalise participants, and leverage EC and industry sponsorship, to structure and expand the unique training programme and advance emerging research areas, combining wet-lab, clinical and Big Data resources with computational and modelling know-how.
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