Listening to the noise: random fluctuations reveal gene network parameters.
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Estimating the stochastic bifurcation structure of cellular networksAdaptive imaging cytometry to estimate parameters of gene networks models in systems and synthetic biologyComputation of steady-state probability distributions in stochastic models of cellular networksEstimation and discrimination of stochastic biochemical circuits from time-lapse microscopy dataQuantifying intrinsic and extrinsic variability in stochastic gene expression modelsA computational framework for analyzing stochasticity in gene expressionInference for Stochastic Chemical Kinetics Using Moment Equations and System Size ExpansionProgramming cells: towards an automated 'Genetic Compiler'Addressing biological uncertainties in engineering gene circuitsA synthetic three-color scaffold for monitoring genetic regulation and noiseStochastic sensitivity analysis and kernel inference via distributional data.Finite state projection based bounds to compare chemical master equation models using single-cell data.ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamicsDynamic characterization of growth and gene expression using high-throughput automated flow cytometry.Identification of models of heterogeneous cell populations from population snapshot data.The finite state projection approach to analyze dynamics of heterogeneous populations.A data-integrated method for analyzing stochastic biochemical networks.Biochemical fluctuations, optimisation and the linear noise approximationModeling dynamics of cell-to-cell variability in TRAIL-induced apoptosis explains fractional killing and predicts reversible resistanceDynamics of protein noise can distinguish between alternate sources of gene-expression variability.Equilibrium distributions of simple biochemical reaction systems for time-scale separation in stochastic reaction networksRibozyme-based insulator parts buffer synthetic circuits from genetic context.Measuring retroactivity from noise in gene regulatory networks.Design and implementation of a biomolecular concentration trackerIterative experiment design guides the characterization of a light-inducible gene expression circuitInferring single-cell gene expression mechanisms using stochastic simulation.Intrinsic noise alters the frequency spectrum of mesoscopic oscillatory chemical reaction systems.Integrating single-molecule experiments and discrete stochastic models to understand heterogeneous gene transcription dynamics.Moment-based inference predicts bimodality in transient gene expression.Defining cooperativity in gene regulation locally through intrinsic noise.Noise Induces Biased Estimation of the Correction Gain.Intercellular Variability in Protein Levels from Stochastic Expression and Noisy Cell Cycle Processes.From analog to digital models of gene regulationExperimental Design for Stochastic Models of Nonlinear Signaling Pathways Using an Interval-Wise Linear Noise Approximation and State Estimation.Quantifying the contribution of chromatin dynamics to stochastic gene expression reveals long, locus-dependent periods between transcriptional bursts.Systematic identification of signal-activated stochastic gene regulation.The Switch in a Genetic Toggle System with Lévy Noise.Modeling stochastic noise in gene regulatory systems.Taking control over microbial populations: Current approaches for exploiting biological noise in bioprocesses.Using noise for model-testing.
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Listening to the noise: random fluctuations reveal gene network parameters.
description
article científic
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article scientifique
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articolo scientifico
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artigo científico
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bilimsel makale
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scientific article published on 13 October 2009
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vedecký článok
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vetenskaplig artikel
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videnskabelig artikel
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vědecký článek
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name
Listening to the noise: random fluctuations reveal gene network parameters.
@en
Listening to the noise: random fluctuations reveal gene network parameters.
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type
label
Listening to the noise: random fluctuations reveal gene network parameters.
@en
Listening to the noise: random fluctuations reveal gene network parameters.
@nl
prefLabel
Listening to the noise: random fluctuations reveal gene network parameters.
@en
Listening to the noise: random fluctuations reveal gene network parameters.
@nl
P2860
P356
P1476
Listening to the noise: random fluctuations reveal gene network parameters
@en
P2093
Brooke Trinh
Mustafa Khammash
P2860
P356
10.1038/MSB.2009.75
P50
P577
2009-10-13T00:00:00Z