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Convergence in parameters and predictions using computational experimental design.

Convergence in parameters and predictions using computational experimental design.

http://www.wikidata.org/entity/Q37561411

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Studying Cellular Signal Transduction with OMIC Technologies Reverse engineering and identification in systems biology: strategies, perspectives and challenges A Bayesian active learning strategy for sequential experimental design in systems biology.Analysis of Practical Identifiability of a Viral Infection Model Designing experiments to understand the variability in biochemical reaction networks.Mathematics of the Integrative Cancer Biology Program.Efficient Bayesian estimates for discrimination among topologically different systems biology models.

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Convergence in parameters and predictions using computational experimental design.

http://www.wikidata.org/entity/Q37561411

description

article científic

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article scientifique

@fr

articolo scientifico

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artigo científico

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bilimsel makale

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scientific article published on August 2013

@en

vedecký článok

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vetenskaplig artikel

@sv

videnskabelig artikel

@da

vědecký článek

@cs

name

Convergence in parameters and predictions using computational experimental design.

@en

Convergence in parameters and predictions using computational experimental design.

@nl

type

label

Convergence in parameters and predictions using computational experimental design.

@en

Convergence in parameters and predictions using computational experimental design.

@nl

prefLabel

Convergence in parameters and predictions using computational experimental design.

@en

Convergence in parameters and predictions using computational experimental design.

@nl

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Convergence in parameters and predictions using computational experimental design

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David R Hagen

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Jacob K White

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20130008

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scholarly article

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10.1098/RSFS.2013.0008

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