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Model-based inference of biochemical parameters and dynamic properties of microbial signal transduction networks

Paper ID Volume ID Publish Year Pages File Format Full-Text
16176 42488 2011 8 PDF Available
Title
Model-based inference of biochemical parameters and dynamic properties of microbial signal transduction networks
Abstract

Because of the inherent uncertainty about quantitative aspects of signalling networks it is of substantial interest to use computational methods that allow inferring non-measurable quantities such as rate constants, from measurable quantities such as changes in protein abundances. We argue that true biochemical parameters like rate constants can generally not be inferred using models due to their non-identifiability. Recent advances, however, facilitate the analysis of parameter identifiability of a given model and automated discrimination of candidate models, both being important techniques to still extract quantitative biological information from experimental data.

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Model-based inference of biochemical parameters and dynamic properties of microbial signal transduction networks
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Publisher
Database: Elsevier - ScienceDirect
Journal: Current Opinion in Biotechnology - Volume 22, Issue 1, February 2011, Pages 109–116
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
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