ESR 9: Modelling of CLEC-2 clustering and signalling

Host: Alacris Theranostics GmbH, Germany

Supervisory Team: Bodo Lange and Christoph Wierling (Alacris Theranostics GmbH, Berlin, Germany), Natalie Poulter and Steve Watson (Birmingham, UK), Prof Bernhard Nieswandt (University of Würzburg, Germany)

Project locations: Alcaris (Year 1, 2 and 3), University of Birmingham, UK (Year 1), University of Würzburg, Germany (Year 3)

Joint PhD Degree: University of Birmingham, UK and University of Würzburg, Germany

Project details: In this project computational modelling and systems biology approaches will be used to study signal transduction pathways that control platelet activation. The role of CLEC-2 clustering and signalling in thrombosis is a subject of intense research. Here we combine omics, imaging and computational modelling to provide further insight into the key molecular processes that control CLEC-2 clustering and associated signalling/function and identify novel targets that impact on platelet regulation controlled by this receptor. A large-scale computational model of a cellular signal transduction will be employed and adapted to investigate the functional effects of perturbations to the CLEC-2-associated signalling network. The model (in the form of ordinary differential equations (ODEs)) will be systematically expanded and parameterised, and through an iterative series of simulations, predictions and experimental validation, models will be optimised and novel molecular targets identified for subsequent screening of small molecule inhibitors.

References: Ogilvie, L.A., Wierling, C., Kessler, T., Lehrach, H., Lange, B.M.H.Predictive Modeling of Drug Treatment in the Area of Personalized Medicine. Cancer Informatics 14(S4) 95–103 doi: 10.4137/CIN.S19330

Schütte, M. et al. Molecular dissection of colorectal cancer in pre-clinical models identifies biomarkers predicting sensitivity to EGFR inhibitors. Nature Communications, 8: doi:10.1038/ncomms14262

Desirable student skills: Systems Biology or Bioinformatics, Python programming skills, basic knowledge of molecular biology, familiarity with working with scientific literature, experience of Matlab.

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