A5046026391- Gene Regulatory Network Analysis
- Microbial Metabolic Engineering and Bioproduction
- Drug-Induced Hepatotoxicity and Protection
- Protein Structure and Dynamics
- Advanced Proteomics Techniques and Applications
- Pharmacogenetics and Drug Metabolism
- PI3K/AKT/mTOR signaling in cancer
- Computational Drug Discovery Methods
- Receptor Mechanisms and Signaling
- NF-κB Signaling Pathways
- Analytical Chemistry and Chromatography
- Homotopy and Cohomology in Algebraic Topology
- Advanced Topics in Algebra
- Protein Kinase Regulation and GTPase Signaling
- Drug Transport and Resistance Mechanisms
- Viral Infectious Diseases and Gene Expression in Insects
- Advanced Control Systems Optimization
- Simulation Techniques and Applications
- Cytokine Signaling Pathways and Interactions
- Genomics, phytochemicals, and oxidative stress
- Malaria Research and Control
- Monoclonal and Polyclonal Antibodies Research
- Advanced Biosensing Techniques and Applications
- Extremum Seeking Control Systems
- Bayesian Modeling and Causal Inference
University of Freiburg
2011-2022
Czech Academy of Sciences, Institute of Physics
2015
Due to the high complexity of biological data it is difficult disentangle cellular processes relying only on intuitive interpretation measurements. A Systems Biology approach that combines quantitative experimental with dynamic mathematical modeling promises yield deeper insights into these processes. Nevertheless, growing and increasing amount data, building realistic reliable models can become a challenging task: quality has be assessed objectively, unknown model parameters need estimated...
In systems biology, one of the major tasks is to tailor model complexity information content data. A useful should describe data and produce well-determined parameter estimates predictions. Too small a will not be able whereas which too large tends overfit measurement errors does provide precise Typically, modified tuned fit data, often results in an oversized model. To restore balance between available measurements, either new has gathered or reduced. this manuscript, we present data-based...
Parameter estimation in ordinary differential equations (ODEs) has manifold applications not only physics but also the life sciences. When estimating ODE parameters from experimentally observed data, modeler is frequently concerned with question of parameter identifiability. The source nonidentifiability tightly related to Lie group symmetries. In present work, we establish a direct search algorithm for determination admitted We clarify relationship between symmetries and nonidentifiability....
In most solid cancers, cells harboring oncogenic mutations represent only a sub-fraction of the entire population. Within this expression level mutated proteins can vary significantly due to cellular variability limiting efficiency targeted therapy. To address causes heterogeneity, we performed systematic analysis one frequently pathways in cancer cells, phosphatidylinositol 3 kinase (PI3K) signaling pathway. Among others PI3K is activated by hepatocyte growth factor (HGF) that regulates...
Analysis of large-scale proteomic data sets requires specialized software tools, tailored toward the requirements individual approaches. Here we introduce an extension open-source solution for analyzing reverse phase protein array (RPPA) data. The R package RPPanalyzer was designed preprocessing followed by basic statistical analyses and visualization. In this update, merged relevant steps into a single user-friendly function included new method background noise correction as well methods...
In a wide variety of research fields, dynamic modeling is employed as an instrument to learn and understand complex systems. The differential equations involved in this process are usually non-linear depend on many parameters whose values determine the characteristics emergent system. inverse problem, i.e., inference or estimation parameter from observed data, interest two points view. First, existence point view, dealing with question whether system able reproduce dynamics for any values....
Abstract About 20% of breast cancer tumors over-express the HER2 receptor. Trastuzumab, an approved drug to treat this type cancer, is a monoclonal antibody directly binding at receptor and ultimately inhibiting cell growth. The goal our study was understand early impact trastuzumab on internalization recycling in HER2-overexpressing line SKBR3. To end, fluorescence microscopy, monitoring amount expression plasma membrane, combined with mathematical modeling derive flux receptors from...
Cells are exposed to oxidative stress and reactive metabolites every day. The Nrf2 signaling pathway responds by upregulation of antioxidants like glutathione (GSH) compensate the insult re-establish homeostasis. Although mechanisms describing interaction between key constituents Nrf2, Keap1 p62 widely reviewed discussed in literature, quantitative dynamic models bringing together these with time-resolved data limited. Here, we present an ordinary differential equation (ODE) based model...
Due to the high complexity of biological data it is difficult disentangle cellular processes relying only on intuitive interpretation measurements.A Systems Biology approach that combines quantitative experimental with dynamic mathematical modeling promises yield deeper insights into these processes.Nevertheless, growing and increasing amount data, building realistic reliable models can become a challenging task: quality has be assessed objectively, unknown model parameters need estimated...
To gain a deeper understanding of biological processes and their relevance in disease, mathematical models are built upon experimental data. Uncertainty the data leads to uncertainties model's parameters turn predictions. Mechanistic dynamic biochemical networks frequently based on nonlinear differential equation systems feature large number parameters, sparse observations model components lack information available Due curse dimensionality, classical sampling approaches propagating...
The B cell antigen receptor (BCR) plays a crucial role in adaptive immunity, since antigen-induced signalling by the BCR leads to activation of and production antibodies during an immune response. However, spatial nano-scale organization on surface prior encounter is still controversial. Here, we fixed murine cells, stained BCRs with immuno-gold visualized distribution gold particles transmission electron microscopy. Approximately 30% were clustered. However low staining efficiency 15%...
Ordinary differential equation models have become a wide-spread approach to analyze dynamical systems and understand underlying mechanisms. Model parameters are often unknown be estimated from experimental data, e.g.~by maximum-likelihood estimation. In particular, of biological contain large number parameters. To reduce the dimensionality parameter space, steady-state information is incorporated in estimation process. For non-linear models, analytical calculation typically leads...
Drug-induced liver injury (DILI) has become a major problem for patients and clinicians, academics the pharmaceutical industry. To date, existing hepatotoxicity test systems are only poorly predictive underlying mechanisms still unclear. One of factors known to amplify is tumor necrosis factor alpha (TNFα), especially due its synergy with commonly used drugs such as diclofenac. However, exact mechanism how diclofenac in combination TNFα induces remains elusive. Here, we combined...
In this paper we consider \mathrm{C}^* -algebraic deformations by actions of \mathbb{R}^d à la Rieffel and show that every state the undeformed algebra can be deformed into a in sense continuous field states. The construction is explicit involves convolution operator with particular Gauß function.
Biological systems are frequently analyzed by means of mechanistic mathematical models. In order to infer model parameters and provide a useful that can be employed for understanding hypothesis testing, the is often calibrated on quantitative, time-resolved data. To do so, it typically important compare experimental measurements over broad time ranges various conditions, e.g. perturbations biological system. However, most established techniques such as Western blot, or quantitative real-time...
Abstract Background High-quality quantitative data is a major limitation in systems biology. The experimental used biology can be assigned to one of the following categories: assays yielding average cell population, high-content single measurements and high-throughput techniques generating for large populations. For modeling purposes, combination from different categories highly desirable order increase number observable species processes thereby maximize identifiability parameters. Results...
When non-linear models are fitted to experimental data, parameter estimates can be poorly constrained albeit being identifiable in principle. This means that along certain paths space, the log-likelihood does not exceed a given statistical threshold but remains bounded. situation, denoted as practical non-identifiability, detected by Monte Carlo sampling or systematic scanning using profile likelihood method. In contrast, any method based on Taylor expansion of around optimum, e.g.,...
A dynamic model based on ordinary differential equations that describes uptake, basolateral and canalicular export of taurocholic acid (TCA) in human HepaRG cells is presented. The highly reproducible inter-assay experimental data were used to reliably estimate parameters. Primary hepatocytes similarly evaluated establish a mathematical model, but with notably higher differences TCA clearance bile canaliculi dynamics. By use the cell line, simultaneous associated sinusoidal efflux, was...
Ordinary differential equations are widely-used in the field of systems biology and chemical engineering to model reaction networks. Numerous techniques have been developed estimate parameters like rate constants, initial conditions or steady state concentrations from time-resolved data. In contrast this countable set parameters, estimation entire courses network components corresponds an innumerable parameters. The approach presented work is able deal with course for extrinsic system inputs...
Abstract In a wide variety of research elds, dynamic modeling is employed as an instrument to learn and understand complex systems. The differential equations involved in this process are usually non-linear depend on many parameters whose values decide upon the characteristics emergent system. inverse problem, i.e. inference or estimation parameter from observed data, interest two points view. First, existence point view, dealing with question whether system able reproduce dynamics for any...
In this paper we consider C*-algebraic deformations a la Rieffel and show that every state of the undeformed algebra can be deformed into in sense continuous field states. The construction is explicit involves convolution operator with particular Gauss function.
ABSTRACT Background The combination antimalarial artefenomel-piperaquine failed to achieve target efficacy in a phase 2b study Africa and Vietnam. We retrospectively evaluated whether characterizing the pharmacological interaction of this volunteer infection (VIS) would have enabled prediction results. Methods Twenty-four healthy adults enrolled over three consecutive cohorts were inoculated with Plasmodium falciparum -infected erythrocytes on day 0. Participants randomized within each...