Partners
Our collaborators and funding partners
Collaborators
We are thankful to our present and past collaborators, including:
Ruedi Aebersold
ETH Zurich
Leonidas G. Alexopoulos
National Technical University of Athens
Eduardo Villablanca
Karolinska Institute
Bernd Bodenmiller
University of Zurich
Julio Banga
(Bio)Process Engineering Group, CSIC
Pedro Beltrao
EMBL-EBI
CoLoMoTo Consortium
in particular Claudine Chaouiya, Denis Thieffry, Tomas Helikar, and Laurence Calzone
Thorsten Cramer
RWTH Aachen
Christian Frezza
MRC – Cambridge
DREAM Challenges
in particular Gustavo Stolovitzky
Mathew Garnett and Ultan McDermott
Sanger Institute
Steffen Klamt
Max Planck Institute
Tamás Korcsmáros
Earlham Institute and Institute of Food Research
Rafael Kramann
RWTH Aachen
Douglas Lauffenburger
Massachusetts Institute of Technology
Christoph Merten
EMBL / EPFL
Alexander Mitsos
RTWH Aachen, Germany
Rainer Pepperkok
EMBL
Miguel Rocha
University of Minho
Anne Siegel
INRIA/IRISA
Peter K. Sorger
Harvard Medical School
Oliver Stegle
EMBL / DKFZ
Funding
| Agency | Duration | Name |
|---|---|---|
| European Research Council | 2024-2030 | Functional cartography of intestinal host-microbiome interactions (CartoHostBug) |
| Deutsche Forschungsgemeinschaft | 2023-present | Establishing a knowledge graph community in biomedical science |
| Deutsche Forschungsgemeinschaft | 2022-present | Deciphering molecular circuits of cardiac remodeling and dysfunction via an integrative reverse approach (B10) |
| Deutsche Forschungsgemeinschaft | 2022-present | INFrastructurefor Biobanking, Data Management and Bioinformatics (INF) |
| Deutsche Forschungsgemeinschaft | 2022-present | MacTrac – Tracking spatio-temporal trajectories of macrophage subtypes in inflammatory demyelination |
| Deutsche Forschungsgemeinschaft | 2022-present | Single-cell and spatial mapping of human diabetic cardiomyopathy |
| European Commission | 2021-2026 | DECIDER: Improved clinical decisions via integrating multiple data levels to overcome chemotherapy resistance in high-grade serous ovarian cancer |
| Sanofi | 2021-2021 | Analysis of essentiality in cancer using CRISPR-Cas9 screenings |
| Bundesministerium für Bildung und Forschung | 2021-2023 | LiSyM-Krebs: Mechanism-based Multiscale Model to Dissect the Tipping Point from Liver Cirrhosis to Hepatocellular Carcinoma |
| Bundesministerium für Bildung und Forschung | 2021-2024 | DeepSC2: Deep learning for single-cell genomics in cancer |
| German Research Foundation | 2021-present | Dissecting IgA nephropathy via integration of multi-omics data |
| Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg | 2020-2022 | BioDATEN : Bioinformatics DATa Environment |
| Bundesministerium für Bildung und Forschung | 2020-2022 | MSCare: A Systems Medicine Approach to Stratification of Cancer Recurrence |
| European Commission | 2020-2024 | StrategyCKD: System omics to unravel the gut-kidney axis in Chronic Kidney Disease |
| European Commission | 2020-2022 | PerMedCoE: HPC Center of Excellence in Personalised Medicine |
| GlaxoSmithKline | 2020-2022 | Analysis of multi-omics and spatial transcriptomics data |
| German Research Foundation | 2020-present | Single cell resolution of human chronic kidney disease for precision medicine in nephrology |
| H2020 Health | 2019-2022 | individualizedPaediatricCure: Cloud-based virtual-patient models for precision paediatric oncology |
| Ministry of Education and Science | 2019-2022 | LaMarcK: Longitudinal Multiomics Characterization of disease using prior Knowledge |
| Klaus-Tschira Stiftung | 2019-2021 | Informatics for Life |
| German Research Foundation | 2018-present | Validating microfluidics-based personalized cancer therapy in mouse models |
| European Commission | 2017-2021 | TransQST: Translational quantitative systems toxicology to improve the understanding of the safety of medicines |
| OncoSignature/Acrivon | 2017-2018 | Analysis of mass spectrometry proteomics and drug treatment |
| BMBF German Ministery of Education and Research | 2016-2019 | SYS4MS: Personalizing health care in Multiple Sclerosis using sytems medicine tools |
| BMBF German Ministery of Education and Research | 2016-2020 | LiSym: Liver systems medicine |
| National Cancer Institute | 2016-2018 | CPTAC DREAM Challenge |
| Research Executive Agency | 2016-2018 | PrECISE: Personalized engine for Cancer integrative study and evaluation |
| Research Executive Agency | 2015-2018 | SyMBioSys : Systematic Models for Biological Systems Engineering Training Network |
| Bayer AG | 2015-2019 | Joint Research Center for Computational Biomedicine |
| Center for Therapeutic Target Validation | 2014-2016 | Novel Target Identification Through Genome-Scale CRISPR-Cas9 Knockout Screening in Human Cancer Cell Lines |
| Center for Therapeutic Target Validation | 2014-2016 | Target identification and validation using pathway activities derived from functional genomics data |
| Research Executive Agency | 2013-2014 | CombiMS: a novel drug discovery method based on systems biology: combination therapy and biomarkers for Multiple Sclerosis |
| Medical Research Council | 2012-2014 | Understanding drug mode of action via statistical integration of functional genomic studies and literature-derived signalling networks |
| Research Executive Agency | 2012-2015 | BioPreDyn: New Bioinformatics Methods and Tools for Data-Driven Predictive Dynamic Modelling in Biotechnological Applications |
| Sanofi | 2011-2012 | Analysis of mass spectrometry phosphoproteomics data in the context of insulin signal processing and functional alterations thereof |