Computational Biology for Infection Research
The Department of “Computational Biology for Infection Research” studies the human microbiome, viral and bacterial pathogens, and human cell lineages within individual patients by analysis of large-scale biological and epidemiological data sets with computational techniques. Focusing on high throughput meta’omics, population genomic and single cell sequencing data, we produce testable hypotheses, such as sets of key sites or relevant genes associated with the presence of a disease, of antibiotic resistance or pathogenic evasion of immune defense. We interact with experimental collaborators to verify our findings and to promote their translation into medical treatment or diagnosis procedures. To achieve its research goals, the department also develops novel algorithms and software.
Leader
Ongoing Grants
2021 “NFDI4Microbiota - National Research Data Infrastructure for Microbiota Research” (DFG)
2021 “GHGA-Microbiota: Increasing the multimodal use of human and microbiome-related omics data” - GHGA Flex Funds Projekt (DFG)
2021 “Hepatitis C Control: Towards prophylaxis and identification of those in need of treatment” (DZIF) (BMBF)
2019 “Paving the way towards individualized vaccination (i.Vacc) - Exploring multi-omics Big Data in the general population based on a digital mHealth cohort” – Volkswagen Stiftung
2019 “Drug discovery and cheminformatics for new anti-infectives (iCA)” – Lower Saxony Doctoral Program
2019 “Rational design of a universal flu vaccine using recombinant neuraminidase” – Global Grand Challenges of the Bill & Melinda Gates Foundation
2019 “GenomeNet: A deep neural network for genomic modelling, semi-supervised classification and imputation” – Computational Life Sciences Call, Bundesministerium für Bildung und Forschung (BMBF)
2019 “RESIST - Resolving Infection Susceptibility“ – Exzellenzcluster 2155, Deutsche Forschungsgemeinschaft (DFG)
2018 “Learning structures in the CRISPR-Cas system using deep learning architectures” – SPP2141 Deutsche Forschungsgemeinschaft (DFG)
2017 “HiGHmed (Heidelberg-Göttingen-Hannover Medizininformatik)“ - Bundesministerium für Bildung und Forschung (BMBF)
2014 “TI Bioressourcen, Biodaten und digitale Gesundheit” (vorher: “TI Bioinformatics Platform“ - Deutsches Zentrum für Infektionsforschung (DZIF) (BMBF)
Concluded Grants
2020 Corona VAC “Proof of concept study of a SARS-COV-2 vaccine based on recombinant spike protein“ - Niedersächsischen Ministerium für Wissenschaft und Kultur (MWK)
2017 “Sparse2Big: Data fusion and imputation from massive sparse data consortium” - Information and Data Science Initiative, Helmholtz Society
2017 “Bioinformatics support for the development of a prophylactic HCV vaccine candidate” - Deutsches Zentrum für Infektionsforschung (DZIF)
2017 “Communities Allied in Infection coalition" - Volkswagen Foundation
2016 “A Method for Tracking CRISPR/Plasmidome Dynamics in Complex Bacterial Communities“ – Research Grant, Deutsche Forschungsgemeinschaft (DFG)
2014 “Isolation and characterization of novel azidophilic archaea (with J. Gescher)” – Deutsche Forschungsgemeinschaft (DFG)
