Sensitivity, robustness, and identifiability in stochastic chemical kinetics models.
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Maximizing the information content of experiments in systems biologyMoment fitting for parameter inference in repeatedly and partially observed stochastic biological modelsEstimation and discrimination of stochastic biochemical circuits from time-lapse microscopy dataCombined model of intrinsic and extrinsic variability for computational network design with application to synthetic biologyA new stochastic model for subgenomic hepatitis C virus replication considers drug resistant mutantsAccelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction NetworksSelection on Network Dynamics Drives Differential Rates of Protein Domain EvolutionInference for Stochastic Chemical Kinetics Using Moment Equations and System Size ExpansionA framework for parameter estimation and model selection from experimental data in systems biology using approximate Bayesian computation.A new efficient approach to fit stochastic models on the basis of high-throughput experimental data using a model of IRF7 gene expression as case study.ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamicsParametric sensitivity analysis for biochemical reaction networks based on pathwise information theory.Biochemical fluctuations, optimisation and the linear noise approximationBayesian model comparison and parameter inference in systems biology using nested samplingMechanistic links between cellular trade-offs, gene expression, and growthStochasticity in Ca2+ increase in spines enables robust and sensitive information coding.Clustering reveals limits of parameter identifiability in multi-parameter models of biochemical dynamics.Iterative experiment design guides the characterization of a light-inducible gene expression circuitRanking of Reactions Based on Sensitivity of Protein Noise Depends on the Choice of Noise Measure.Integrating single-molecule experiments and discrete stochastic models to understand heterogeneous gene transcription dynamics.Experimental Design for Stochastic Models of Nonlinear Signaling Pathways Using an Interval-Wise Linear Noise Approximation and State Estimation.A large-scale stochastic spatiotemporal model for Aedes albopictus-borne chikungunya epidemiology.Convergence in parameters and predictions using computational experimental design.Model-based design of experiments for cellular processes.A confidence building exercise in data and identifiability: Modeling cancer chemotherapy as a case study.Model distinguishability and inference robustness in mechanisms of cholera transmission and loss of immunity.Parameter identification using stochastic simulations reveals a robustness in CD95 apoptotic response.Bootstrapping least-squares estimates in biochemical reaction networks.Long-time analytic approximation of large stochastic oscillators: Simulation, analysis and inference.Bayesian design strategies for synthetic biologyStatistical analysis of nonlinear dynamical systems using differential geometric sampling methodsComparison of finite difference based methods to obtain sensitivities of stochastic chemical kinetic models.How to deal with parameters for whole-cell modelling.Feedback mechanisms control coexistence in a stem cell model of acute myeloid leukaemia.Bayesian experimental design for models with intractable likelihoods.Information processing by simple molecular motifs and susceptibility to noiseDesigning experiments to understand the variability in biochemical reaction networks.Fisher information metric for the Langevin equation and least informative models of continuous stochastic dynamics.A relative entropy rate method for path space sensitivity analysis of stationary complex stochastic dynamics.A general moment expansion method for stochastic kinetic models.
P2860
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P2860
Sensitivity, robustness, and identifiability in stochastic chemical kinetics models.
description
2011 nî lūn-bûn
@nan
2011 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Sensitivity, robustness, and identifiability in stochastic chemical kinetics models.
@ast
Sensitivity, robustness, and identifiability in stochastic chemical kinetics models.
@en
type
label
Sensitivity, robustness, and identifiability in stochastic chemical kinetics models.
@ast
Sensitivity, robustness, and identifiability in stochastic chemical kinetics models.
@en
prefLabel
Sensitivity, robustness, and identifiability in stochastic chemical kinetics models.
@ast
Sensitivity, robustness, and identifiability in stochastic chemical kinetics models.
@en
P2093
P2860
P356
P1476
Sensitivity, robustness, and identifiability in stochastic chemical kinetics models
@en
P2093
Maria J Costa
Michael P H Stumpf
Michał Komorowski
P2860
P304
P356
10.1073/PNAS.1015814108
P407
P50
P577
2011-05-06T00:00:00Z