[HTML][HTML] Systematic calibration of a cell signaling network model
Background Mathematical modeling is being applied to increasingly complex biological
systems and datasets; however, the process of analyzing and calibrating against …
systems and datasets; however, the process of analyzing and calibrating against …
A consensus approach for estimating the predictive accuracy of dynamic models in biology
AF Villaverde, S Bongard, K Mauch, D Müller… - Computer methods and …, 2015 - Elsevier
Mathematical models that predict the complex dynamic behaviour of cellular networks are
fundamental in systems biology, and provide an important basis for biomedical and …
fundamental in systems biology, and provide an important basis for biomedical and …
Model calibration and uncertainty analysis in signaling networks
T Heinemann, A Raue - Current opinion in biotechnology, 2016 - Elsevier
Highlights•Model calibration for mechanistic signaling models is well established.•An
appropriate objective function is pivotal for meaningful model calibration.•Robust …
appropriate objective function is pivotal for meaningful model calibration.•Robust …
Computational processing and error reduction strategies for standardized quantitative data in biological networks
M Schilling, T Maiwald, S Bohl, M Kollmann… - The FEBS …, 2005 - Wiley Online Library
High‐quality quantitative data generated under standardized conditions is critical for
understanding dynamic cellular processes. We report strategies for error reduction, and …
understanding dynamic cellular processes. We report strategies for error reduction, and …
[HTML][HTML] Performance of objective functions and optimisation procedures for parameter estimation in system biology models
Mathematical modelling of signalling pathways aids experimental investigation in system
and synthetic biology. Ever increasing data availability prompts the development of large …
and synthetic biology. Ever increasing data availability prompts the development of large …
[HTML][HTML] Hybrid optimization method with general switching strategy for parameter estimation
Background Modeling and simulation of cellular signaling and metabolic pathways as
networks of biochemical reactions yields sets of non-linear ordinary differential equations …
networks of biochemical reactions yields sets of non-linear ordinary differential equations …
Differential simulated annealing: a robust and efficient global optimization algorithm for parameter estimation of biological networks
Ordinary differential equations (ODEs) are widely used to model the dynamic properties of
biological networks. Due to the complexity of biological networks and limited quantitative …
biological networks. Due to the complexity of biological networks and limited quantitative …
Parameter identification, experimental design and model falsification for biological network models using semidefinite programming
One of the most challenging tasks in systems biology is parameter identification from
experimental data. In particular, if the available data are noisy, the resulting parameter …
experimental data. In particular, if the available data are noisy, the resulting parameter …
CaliPro: A Calibration Protocol That Utilizes Parameter Density Estimation to Explore Parameter Space and Calibrate Complex Biological Models
Introduction Mathematical and computational modeling have a long history of uncovering
mechanisms and making predictions for biological systems. However, to create a model that …
mechanisms and making predictions for biological systems. However, to create a model that …
Statistical model checking based calibration and analysis of bio-pathway models
We present a statistical model checking (SMC) based framework for studying ordinary
differential equation (ODE) models of bio-pathways. We address cell-to-cell variability …
differential equation (ODE) models of bio-pathways. We address cell-to-cell variability …