A5052831097- Gene Regulatory Network Analysis
- Neural dynamics and brain function
- Neurological disorders and treatments
- EEG and Brain-Computer Interfaces
- Chaos control and synchronization
- Functional Brain Connectivity Studies
- Neuroscience and Neural Engineering
- Microbial Metabolic Engineering and Bioproduction
- Neural Networks and Applications
- Bioinformatics and Genomic Networks
- Complex Systems and Time Series Analysis
- Nonlinear Dynamics and Pattern Formation
- Blind Source Separation Techniques
- Cytokine Signaling Pathways and Interactions
- Traumatic Brain Injury and Neurovascular Disturbances
- Control Systems and Identification
- HER2/EGFR in Cancer Research
- Epilepsy research and treatment
- Protein Structure and Dynamics
- Fault Detection and Control Systems
- Monoclonal and Polyclonal Antibodies Research
- Computational Drug Discovery Methods
- Light effects on plants
- Parkinson's Disease Mechanisms and Treatments
- Plant Molecular Biology Research
University of Freiburg
2016-2025
Czech Academy of Sciences, Institute of Physics
2009-2024
Heidelberg University
2009-2023
University Hospital Heidelberg
2010-2023
German Cancer Research Center
2009-2018
Fraunhofer Chalmers Research Centre for Industrial Mathematics
2014
Linköping University
2011-2013
École Polytechnique Fédérale de Lausanne
2013
University Medical Center Freiburg
1994-2012
Institute for Physics
2012
Abstract Motivation: Mathematical description of biological reaction networks by differential equations leads to large models whose parameters are calibrated in order optimally explain experimental data. Often only parts the model can be observed directly. Given a that sufficiently describes measured data, it is important infer how well determined amount and quality This knowledge essential for further investigation predictions. For this reason major topic modeling identifiability analysis....
Mathematical reaction-diffusion models have been suggested to describe formation of animal pigmentation patterns and distribution epidermal appendages. However, the crucial signals in vivo mechanisms are still elusive. Here we identify WNT its inhibitor DKK as primary determinants murine hair follicle spacing, using a combined experimental computational modeling approach. Transgenic overexpression reduces overall appendage density. Moderate suppression endogenous signaling forces follicles...
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...
Resilience is still often viewed as a unitary personality construct that, kind of antinosological entity, protects individuals against stress-related mental problems. However, increasing evidence indicates that maintaining health in the face adversity results from complex and dynamic processes adaptation to stressors involve activation several separable protective factors. Such resilience factors can reside at biological, psychological, social levels may include stable predispositions (such...
Abstract Summary: Modeling of dynamical systems using ordinary differential equations is a popular approach in the field biology. Two most critical steps this are to construct models biochemical reaction networks for large datasets and complex experimental conditions perform efficient reliable parameter estimation model fitting. We present modeling environment MATLAB that pioneers these challenges. The numerically expensive parts calculations such as solving associated sensitivity system...
Engineering liquid-liquid phase separation into synthetic and optogenetic transcription factors increases gene expression.
Considerable progress has been made in identifying the molecular composition of complex signaling networks controlling cell proliferation, differentiation, and survival. However, to discover general building principles predict dynamic behavior networks, it is necessary develop quantitative models based on experimental observations. Here we report a mathematical model core module Janus family kinases (JAK)–signal transducer activator transcription (STAT) pathway time-resolved measurements...
We review the problem of estimating parameters and unobserved trajectory components from noisy time series measurements continuous nonlinear dynamical systems. It is first shown that in parameter estimation techniques do not take measurement errors explicitly into account, like regression approaches, can produce inaccurate estimates. Another for chaotic systems cost functions have to be minimized estimate states are so complex common optimization routines may fail. show inclusion information...
Abstract Motivation: Modelers in Systems Biology need a flexible framework that allows them to easily create new dynamic models, investigate their properties and fit several experimental datasets simultaneously. Multi-experiment-fitting is powerful approach estimate parameter values, check the validity of given model, discriminate competing model hypotheses. It requires high-performance integration ordinary differential equations robust optimization. Results: We here present comprehensive...
Article7 April 2009Open Access Systems-level interactions between insulin–EGF networks amplify mitogenic signaling Nikolay Borisov Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, PA, USA Search for more papers by this author Edita Aksamitiene Anatoly Kiyatkin Stefan Legewie Institute Theoretical Humboldt Berlin, Germany Jan Berkhout Maiwald Freiburg Advanced Science, University Freiburg, Nikolai P Kaimachnikov Biophysics, Russian Academy...