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Gene Regulatory Networks

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Cover of 'Gene Regulatory Networks'

Table of Contents

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    Book Overview
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    Chapter 1 Gene Regulatory Network Inference: An Introductory Survey
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    Chapter 2 Statistical Network Inference for Time-Varying Molecular Data with Dynamic Bayesian Networks
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    Chapter 3 Overview and Evaluation of Recent Methods for Statistical Inference of Gene Regulatory Networks from Time Series Data
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    Chapter 4 Whole-Transcriptome Causal Network Inference with Genomic and Transcriptomic Data
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    Chapter 5 Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical Study in Small Networks
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    Chapter 6 A Multiattribute Gaussian Graphical Model for Inferring Multiscale Regulatory Networks: An Application in Breast Cancer
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    Chapter 7 Integrative Approaches for Inference of Genome-Scale Gene Regulatory Networks
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    Chapter 8 Unsupervised Gene Network Inference with Decision Trees and Random Forests
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    Chapter 9 Tree-Based Learning of Regulatory Network Topologies and Dynamics with Jump3
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    Chapter 10 Network Inference from Single-Cell Transcriptomic Data
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    Chapter 11 Inferring Gene Regulatory Networks from Multiple Datasets
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    Chapter 12 Unsupervised GRN Ensemble
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    Chapter 13 Learning Differential Module Networks Across Multiple Experimental Conditions
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    Chapter 14 Stability in GRN Inference
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    Chapter 15 Gene Regulatory Networks: A Primer in Biological Processes and Statistical Modelling
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    Chapter 16 Scalable Inference of Ordinary Differential Equation Models of Biochemical Processes
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Chapter title
Gene Regulatory Networks: A Primer in Biological Processes and Statistical Modelling
Chapter number 15
Book title
Gene Regulatory Networks
Published by
Humana Press, New York, NY, December 2018
DOI 10.1007/978-1-4939-8882-2_15
Pubmed ID
Book ISBNs
978-1-4939-8881-5, 978-1-4939-8882-2
Authors

Olivia Angelin-Bonnet, Patrick J. Biggs, Matthieu Vignes, Angelin-Bonnet, Olivia, Biggs, Patrick J., Vignes, Matthieu

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 24%
Student > Ph. D. Student 7 19%
Student > Bachelor 3 8%
Student > Doctoral Student 2 5%
Student > Postgraduate 2 5%
Other 6 16%
Unknown 8 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 27%
Physics and Astronomy 5 14%
Computer Science 3 8%
Agricultural and Biological Sciences 3 8%
Mathematics 1 3%
Other 5 14%
Unknown 10 27%