Browsing Publications of the research group Chemical Biology (CBIO) by Authors
From binary to multivalued to continuous models: the lac operon as a case study.Franke, Raimo; Theis, Fabian J; Klamt, Steffen; Helmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany. (2010-12-14)Using the lac operon as a paradigmatic example for a gene regulatory system in prokaryotes, we demonstrate how qualitative knowledge can be initially captured using simple discrete (Boolean) models and then stepwise refined to multivalued logical models and finally to continuous (ODE) models. At all stages, signal transduction and transcriptional regulation is integrated in the model description. We first show the potential benefit of a discrete binary approach and discuss then problems and limitations due to indeterminacy arising in cyclic networks. These limitations can be partially circumvented by using multilevel logic as generalization of the Boolean framework enabling one to formulate a more realistic model of the lac operon. Ultimately a dynamic description is needed to fully appreciate the potential dynamic behavior that can be induced by regulatory feedback loops. As a very promising method we show how the use of multivariate polynomial interpolation allows transformation of the logical network into a system of ordinary differential equations (ODEs), which then enables the analysis of key features of the dynamic behavior.
LifeTime and improving European healthcare through cell-based interceptive medicine.Rajewsky, Nikolaus; Almouzni, Geneviève; Gorski, Stanislaw A; Aerts, Stein; Amit, Ido; Bertero, Michela G; Bock, Christoph; Bredenoord, Annelien L; Cavalli, Giacomo; Chiocca, Susanna; et al. (NPG, 2020-09-07)Here we describe the LifeTime Initiative, which aims to track, understand and target human cells during the onset and progression of complex diseases, and to analyse their response to therapy at single-cell resolution. This mission will be implemented through the development, integration and application of single-cell multi-omics and imaging, artificial intelligence and patient-derived experimental disease models during the progression from health to disease. The analysis of large molecular and clinical datasets will identify molecular mechanisms, create predictive computational models of disease progression, and reveal new drug targets and therapies. The timely detection and interception of disease embedded in an ethical and patient-centred vision will be achieved through interactions across academia, hospitals, patient associations, health data management systems and industry. The application of this strategy to key medical challenges in cancer, neurological and neuropsychiatric disorders, and infectious, chronic inflammatory and cardiovascular diseases at the single-cell level will usher in cell-based interceptive medicine in Europe over the next decade.