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Displaying results 141 to 150 of 157.
Herrenhausen Symposium
Event Archive Herrenhausen Symposium Individualised Infection Medicine: The Future is Now Infektionen sind nach wie vor eine der Haupttodesursachen weltweit. Individuell zugeschnittene Vorsorge und Therapien versprechen neue Heilungsmöglichkeiten. Wie aber…
Data protection
Data protection Data protection Thank you for your interest in our website. The Helmholtz Centre for Infection Research (HZI) takes the protection of personal data very seriously. It is possible to use our website without providing any personal data. This…
Beate Junk
Imprint
Imprint according to the following German regulations: § 6 TDG, § 10 MDStV Publisher Helmholtz-Zentrum für Infektionsforschung GmbH (Helmholtz Centre for Infection Research) Inhoffenstraße 7 38124 Braunschweig Telefon: 0531 6181-0 Telefax: 0531 6181-2655…
ERC Proof of Concept Grant for Yang Li
“Prof. Dr. Yang Li impressively combines insights from the life sciences and data science in her research. In doing so, she is laying the foundation for new possibilities for individually adapted diagnoses and therapies in medicine. As head of the Centre for…
Jobs
Jobs © AdobeStock_294726409 Initiativbewerbungen Become part of the team We are always interested in receiving applications from motivated candidates. More © HZI PhD Program Initiative "Curiosity is infectious" With the initiative “Curiosity is infectious”,…
CAIMed Group 1b: AI and Bioinformatics
The identification of genetic risk factors and their molecular signaling pathways as well as the development of predictive models for disease progression and severity are crucial for progress in the understanding and individualized treatment of diseases. At the MHH, existing and planned patient cohorts with state-of-the-art (single-cell) multi-omics data are available. The bioinformatics junior research group will focus on the pre-processing of molecular data in order to create standardized data sets for the analyses of the other CAIMed junior research groups. The aim is to integrate this data on an unprecedented scale using innovative AI methods. These include the identification of factors that correlate with disease severity and progression using causal inference methods. Furthermore, the investigation of cell type-specific genetic effects on molecular characteristics will be carried out using the "deconvolution" method. Finally, mathematical models such as support vector machines will be developed to predict individual reactions to diseases/treatments and thus create a molecular basis for the stratification of patient groups. The aim is to promote the implementation of these mathematical models in medical treatment or diagnostic procedures as a crucial first step towards individualized prevention. Close cooperation with the Integrative Multi-Omics Data group is planned.
