Gaussian process regression bootstrapping: exploring the effects of uncertainty in time course data
about
A new stochastic kriging method for modeling multi-source exposure-response data in toxicology studiesParameter trajectory analysis to identify treatment effects of pharmacological interventionsPredicting chemoinsensitivity in breast cancer with 'omics/digital pathology data fusionTailored parameter optimization methods for ordinary differential equation models with steady-state constraintsCombining test statistics and models in bootstrapped model rejection: it is a balancing actAccelerating Bayesian hierarchical clustering of time series data with a randomised algorithm.A method to identify differential expression profiles of time-course gene data with Fourier transformationA framework for parameter estimation and model selection from experimental data in systems biology using approximate Bayesian computation.A simple approach to ranking differentially expressed gene expression time courses through Gaussian process regressionBayesian hierarchical clustering for microarray time series data with replicates and outlier measurements.Estimating replicate time shifts using Gaussian process regression.DREAM4: Combining genetic and dynamic information to identify biological networks and dynamical modelsTopological sensitivity analysis for systems biologyCombinatorial code governing cellular responses to complex stimuli.Gaussian process test for high-throughput sequencing time series: application to experimental evolution.Validation and selection of ODE based systems biology models: how to arrive at more reliable decisions.A simulation framework for correlated count data of features subsets in high-throughput sequencing or proteomics experiments.Gaussian process based modeling and experimental design for sensor calibration in drifting environmentsApplications of analysis of dynamic adaptations in parameter trajectoriesModel of Host-Pathogen Interaction Dynamics Links In Vivo Optical Imaging and Immune Responses.Designing attractive models via automated identification of chaotic and oscillatory dynamical regimes.Evaluating optimal therapy robustness by virtual expansion of a sample population, with a case study in cancer immunotherapy.A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series.Derivative processes for modelling metabolic fluxes.Bayesian correlated clustering to integrate multiple datasets.Detecting time periods of differential gene expression using Gaussian processes: an application to endothelial cells exposed to radiotherapy dose fraction.
P2860
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P2860
Gaussian process regression bootstrapping: exploring the effects of uncertainty in time course data
description
2009 nî lūn-bûn
@nan
2009 թուականի Մարտին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի մարտին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
Gaussian process regression bo ...... ncertainty in time course data
@ast
Gaussian process regression bo ...... ncertainty in time course data
@en
type
label
Gaussian process regression bo ...... ncertainty in time course data
@ast
Gaussian process regression bo ...... ncertainty in time course data
@en
prefLabel
Gaussian process regression bo ...... ncertainty in time course data
@ast
Gaussian process regression bo ...... ncertainty in time course data
@en
P2860
P356
P1433
P1476
Gaussian process regression bo ...... ncertainty in time course data
@en
P2093
Michael P H Stumpf
P2860
P304
P356
10.1093/BIOINFORMATICS/BTP139
P407
P50
P577
2009-03-16T00:00:00Z