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Uncertainty in Biology

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Cover of 'Uncertainty in Biology'

Table of Contents

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    Book Overview
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    Chapter 1 An Introduction to Uncertainty in the Development of Computational Models of Biological Processes
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    Chapter 2 Reverse Engineering Under Uncertainty
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    Chapter 3 Probabilistic Computational Causal Discovery for Systems Biology
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    Chapter 4 Stochastic Modeling and Simulation Methods for Biological Processes: Overview
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    Chapter 5 The Experimental Side of Parameter Estimation
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    Chapter 6 Statistical Data Analysis and Modeling
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    Chapter 7 Optimization in Biology Parameter Estimation and the Associated Optimization Problem
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    Chapter 8 Interval Methods
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    Chapter 9 Model Extension and Model Selection
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    Chapter 10 Bayesian Model Selection Methods and Their Application to Biological ODE Systems
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    Chapter 11 Sloppiness and the Geometry of Parameter Space
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    Chapter 12 Modeling and Model Simplification to Facilitate Biological Insights and Predictions
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    Chapter 13 Sensitivity Analysis by Design of Experiments
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    Chapter 14 Waves in Spatially-Disordered Neural Fields: A Case Study in Uncertainty Quantification
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    Chapter 15 In-Silico Models of Trabecular Bone: A Sensitivity Analysis Perspective
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    Chapter 16 Neuroswarm: A Methodology to Explore the Constraints that Function Imposes on Simulation Parameters in Large-Scale Networks of Biological Neurons
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    Chapter 17 Prediction Uncertainty Estimation Despite Unidentifiability: An Overview of Recent Developments
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    Chapter 18 Computational Modeling Under Uncertainty: Challenges and Opportunities
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Title
Uncertainty in Biology
Published by
Springer, October 2015
DOI 10.1007/978-3-319-21296-8
ISBNs
978-3-31-921295-1, 978-3-31-921296-8
Authors

Laing, Carlo R.

Editors

Liesbet Geris, David Gomez-Cabrero

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Mexico 1 <1%
Germany 1 <1%
Unknown 96 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 29%
Researcher 17 17%
Student > Master 14 14%
Professor 7 7%
Student > Bachelor 7 7%
Other 14 14%
Unknown 13 13%
Readers by discipline Count As %
Engineering 17 17%
Computer Science 14 14%
Agricultural and Biological Sciences 11 11%
Biochemistry, Genetics and Molecular Biology 8 8%
Mathematics 7 7%
Other 27 27%
Unknown 17 17%