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Bacterial Molecular Networks

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Cover of 'Bacterial Molecular Networks'

Table of Contents

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    Book Overview
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    Chapter 1 Bacterial molecular networks: bridging the gap between functional genomics and dynamical modelling.
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    Chapter 2 Bacterial Interactomes: From Interactions to Networks
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    Chapter 3 Bacterial Molecular Networks
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    Chapter 4 Prokaryote genome fluidity: toward a system approach of the mobilome.
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    Chapter 5 Reticulate Classification of Mosaic Microbial Genomes Using NeAT Website
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    Chapter 6 From Metabolic Reactions to Networks and Pathways
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    Chapter 7 Predicting Metabolic Pathways by Sub-network Extraction
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    Chapter 8 Directed Module Detection in a Large-Scale Expression Compendium
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    Chapter 9 Using Phylogenetic Profiles to Predict Functional Relationships
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    Chapter 10 Extracting Regulatory Networks of Escherichia coli from RegulonDB
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    Chapter 11 Browsing Metabolic and Regulatory Networks with BioCyc
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    Chapter 12 Algorithms for Systematic Identification of Small Subgraphs
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    Chapter 13 The Degree Distribution of Networks: Statistical Model Selection
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    Chapter 14 MAVisto: A Tool for Biological Network Motif Analysis
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    Chapter 15 Using MCL to Extract Clusters from Networks
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    Chapter 16 Protein Complex Prediction with RNSC
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    Chapter 17 Network Analysis and Protein Function Prediction with the PRODISTIN Web Site
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    Chapter 18 Using the NeAT Toolbox to Compare Networks to Networks, Clusters to Clusters, and Network to Clusters
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    Chapter 19 Analyzing Biological Data Using R: Methods for Graphs and Networks
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    Chapter 20 Detecting Structural Invariants in Biological Reaction Networks
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    Chapter 21 Petri Nets in Snoopy: A Unifying Framework for the Graphical Display, Computational Modelling, and Simulation of Bacterial Regulatory Networks
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    Chapter 22 Genetic Network Analyzer: A Tool for the Qualitative Modeling and Simulation of Bacterial Regulatory Networks
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    Chapter 23 Logical Modelling of Gene Regulatory Networks with GINsim.
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    Chapter 24 Modelling the Evolution of Mutualistic Symbioses
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    Chapter 25 Modelling the Onset of Virulence in Pathogenic Bacteria
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    Chapter 26 Spatial and Stochastic Cellular Modeling with the Smoldyn Simulator
Attention for Chapter 3: Bacterial Molecular Networks
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Citations

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Chapter title
Bacterial Molecular Networks
Chapter number 3
Book title
Bacterial Molecular Networks
Published in
Methods in molecular biology, January 2012
DOI 10.1007/978-1-61779-361-5_3
Pubmed ID
Book ISBNs
978-1-61779-360-8, 978-1-61779-361-5
Authors

Shannon J. Williamson, Shibu Yooseph, Williamson, Shannon J., Yooseph, Shibu

Abstract

Metagenomics is revolutionizing the field of microbial ecology through techniques that eliminate the prerequisite of culturing. Metagenomic studies of microbial populations in different environments reveal the incredible diversity and adaptive capabilities of these organisms. With the advent of cheaper, high-throughput sequencing technologies, these studies are also producing vast amounts of sequence data. Here, we discuss the different components of a metagenomic study including sample collection, DNA extraction, sequencing, and informatics. We highlight their issues and challenges, and review the solutions that are currently in use. We conclude with examples of metagenomic studies conducted on environments of varying complexities.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 4 7%
United States 2 3%
Portugal 1 2%
United Kingdom 1 2%
Sweden 1 2%
Unknown 52 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 34%
Student > Ph. D. Student 12 20%
Student > Master 5 8%
Student > Doctoral Student 4 7%
Student > Bachelor 4 7%
Other 11 18%
Unknown 4 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 51%
Biochemistry, Genetics and Molecular Biology 6 10%
Environmental Science 4 7%
Computer Science 4 7%
Immunology and Microbiology 4 7%
Other 8 13%
Unknown 4 7%