
New phone system at TWINCORE
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TWINCORE was founded in 2008 by the Helmholtz Centre for Infection Research and the Hannover Medical School. We combine the expertise of medical professionals and scientists from a wide range of disciplines to find answers to the pressing questions in infection research. Our focus: translational research – the bridge between basic science and clinical application.

Some extension numbers have changed.

zukunft.niedersachsen provides €2.7 million in funding for joint project on rare diseases

€100,000 from the German Society for Parkinson's Disease and Movement Disorders
We conduct translational infection research to improve the prevention, diagnosis and treatment of infectious diseases in humans. We focus on three areas that characterize our research work. Find out here how we proceed and what results we achieve.
Under the leadership of our best scientists, various labs are working on different projects within our research topics.
Ilan S, Bartsch Y, Jung W, Kliuchnikov E, Roy V, Bonifer R, Walker-Sperling V, Borducchi E, Nkolola J, Lauffenburger D, Stieh D, Barouch D, Julg B
Koeken V, Nissen T, Birk N, Boahen C, van Crevel R, Kumar V, Li Y, Aaby P, Benn C, Netea M
Vadaq N, Groenendijk A, Dos Santos J, Mehta K, Wit F, Vos W, Blaauw M, van Eekeren L, Lambrechts L, Rutsaert S, Nelwan E, Xu C, Joosten L, de Mast Q, Matzaraki V, van Lunzen J, Rokx C, Verbon A, Netea M, Vandekerckhove L, van der Ven A
In this project, antibodies that help to ward off infections are being investigated in more detail. The aim is to find characteristics that have a protective effect against certain pathogens by comparing different antibody profiles in infections and vaccinations.
Older people are at high risk of a poor immune response to the flu vaccine. Together with partners, we are looking for biomarkers and risk factors for this inadequate response and are investigating ways to improve the vaccination response.
We are investigating how antibodies protect against HCV infection, in particular what properties they have during a healing infection. The aim is to identify antibodies that are important for an effective vaccine against HCV.
Thanks to high-throughput sequencing, genome sequences of hundreds of bacterial strains can be analyzed efficiently, revealing differences of up to 60 % in gene content, as in E. coli. With the help of machine learning, we want to better predict the functions of accessory genes and decipher their contribution to survival in specialized niches.

