Management of data communication
The data set collected by the project e:KID is highly complex: It is time-resolved, heterogeneous, high-dimensional, and pertains to various clinical conditions of patients after renal transplantation. In order to successfully identify novel biomarkers identification and develop prognostic models, fast and effective collection of data and clinical know-how is essential. This subproject focusses on the management of data collection and integration, and on the development of adequate strategies of biomarker identification and evaluation based on clinical guidelines and state-of-the-art clinical procedures. Moreover, this subproject contributes methods of machine learning and feature selection to the data mining efforts, and participates also in the mathematical modeling of the interaction between immunosuppressive medication and post-transplant complications, laying special emphasis on the humoral immune response.