Abstract—The paper concerns the problem of fitting mathematical models of cell signaling pathways. Such models frequently take the form of sets of nonlinear ordinary differential equations. While the model is continuous in time, the performance index used in the fitting procedure involves measurements taken at discrete time moments. Adjoint sensitivity analysis is a tool which can be used for finding the gradient of a performance index in the space of parameters of the model. In the paper, a structural formulation of adjoint sensitivity analysis called the Generalized Backpropagation Through Time (GBPTT) is used. The method is especially suited for hybrid, continuous-discrete time systems. As an example, we use the mathematical model of the...
BACKGROUND: The "inverse" problem is related to the determination of unknown causes on the bases o...
Sensitivity analysis is an important tool that can be used to assess and improve the design and accu...
Differential sensitivity analysis is indispensable in fitting parameters, understanding uncertainty,...
The paper is focused on sensitivity analysis of large-scale models of biological systems that descri...
Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equat...
Mathematical modelling offers a variety of useful techniques to help in understanding the intrinsic ...
The paper is focused on application of sensitivity methods to analysis of signaling pathway models. ...
<div><p>In systems biology, a mathematical description of signal transduction processes is used to g...
Modeling the dynamic behavior of signal transduction pathways is an important topic in systems biolo...
Motivation: Cellular information processing can be described mathematically using differential equat...
The modeling of signal transduction pathways is a task of systems biology. However, such a task is v...
Abstract Background Mathematical modeling is being applied to increasingly complex biological system...
One of possible approaches to modeling of cell signaling pathways is to use a set of nonlinear ODEs ...
The last decade has seen an explosion in models that describe phenomena in systems medicine. Such mo...
Recent advances in quantification methods of regulatory and signaling gene networks has lead to an i...
BACKGROUND: The "inverse" problem is related to the determination of unknown causes on the bases o...
Sensitivity analysis is an important tool that can be used to assess and improve the design and accu...
Differential sensitivity analysis is indispensable in fitting parameters, understanding uncertainty,...
The paper is focused on sensitivity analysis of large-scale models of biological systems that descri...
Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equat...
Mathematical modelling offers a variety of useful techniques to help in understanding the intrinsic ...
The paper is focused on application of sensitivity methods to analysis of signaling pathway models. ...
<div><p>In systems biology, a mathematical description of signal transduction processes is used to g...
Modeling the dynamic behavior of signal transduction pathways is an important topic in systems biolo...
Motivation: Cellular information processing can be described mathematically using differential equat...
The modeling of signal transduction pathways is a task of systems biology. However, such a task is v...
Abstract Background Mathematical modeling is being applied to increasingly complex biological system...
One of possible approaches to modeling of cell signaling pathways is to use a set of nonlinear ODEs ...
The last decade has seen an explosion in models that describe phenomena in systems medicine. Such mo...
Recent advances in quantification methods of regulatory and signaling gene networks has lead to an i...
BACKGROUND: The "inverse" problem is related to the determination of unknown causes on the bases o...
Sensitivity analysis is an important tool that can be used to assess and improve the design and accu...
Differential sensitivity analysis is indispensable in fitting parameters, understanding uncertainty,...