Objective
Every year chronic infections in patients due to biofilm formation of pathogenic bacteria are a multi-billion Euro burden to national healthcare systems. Despite improvements in technology and medical services, morbidity and mortality due to chronic infections have remained unchanged over the past decades. The emergence of a chronic infection disease burden calls for the development of modern diagnostics for biofilm resistance profiling and new therapeutic strategies to eradicate biofilm-associated infections. However, many unsuccessful attempts to address this need teach us that alternative perspectives are needed to meet the challenges.
The project is committed to develop innovative diagnostics and to strive for therapeutic solutions in patients suffering from biofilm-associated infections. The objective is to apply data-driven science to unlock the potential of microbial genomics. This new approach uses tools of advanced microbiological genomics and machine learning in genome-wide association studies on an existing unprecedentedly large dataset. This dataset has been generated in my group within the last five years and comprises sequence variation and gene expression information of a plethora of clinical Pseudomonas aeruginosa isolates. The wealth of patterns and characteristics of biofilm resistance are invisible at a smaller scale and will be interpreted within context and domain-specific knowledge.
The unique combination of basic molecular biology research, technology-driven approaches and data-driven science allows pioneer research dedicated to advance strategies to combat biofilm-associated infections. My approach does not only provide a prediction of biofilm resistance based on the bacteria´s genotype but also holds promise to transform treatment paradigms for the management of chronic infections and by interference with bacterial stress responses will promote the effectiveness of antimicrobials in clinical use to eradicate biofilm infections.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences data science
- natural sciences biological sciences genetics
- natural sciences biological sciences microbiology bacteriology
- natural sciences computer and information sciences artificial intelligence machine learning
- natural sciences biological sciences molecular biology
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-COG - Consolidator Grant
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2016-COG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
38124 Braunschweig
Germany
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.