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Bacterial Molecular Networks

Overview of attention for book
Cover of 'Bacterial Molecular Networks'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Bacterial molecular networks: bridging the gap between functional genomics and dynamical modelling.
  3. Altmetric Badge
    Chapter 2 Bacterial Interactomes: From Interactions to Networks
  4. Altmetric Badge
    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
  7. Altmetric Badge
    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
  21. Altmetric Badge
    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
  23. Altmetric Badge
    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.
  25. Altmetric Badge
    Chapter 24 Modelling the Evolution of Mutualistic Symbioses
  26. Altmetric Badge
    Chapter 25 Modelling the Onset of Virulence in Pathogenic Bacteria
  27. Altmetric Badge
    Chapter 26 Spatial and Stochastic Cellular Modeling with the Smoldyn Simulator
Attention for Chapter 2: Bacterial Interactomes: From Interactions to Networks
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Chapter title
Bacterial Interactomes: From Interactions to Networks
Chapter number 2
Book title
Bacterial Molecular Networks
Published in
Methods in molecular biology, January 2012
DOI 10.1007/978-1-61779-361-5_2
Pubmed ID
Book ISBNs
978-1-61779-360-8, 978-1-61779-361-5
Authors

Emmanuelle Bouveret, Christine Brun, Bouveret, Emmanuelle, Brun, Christine

Abstract

In order to ensure their function(s) in the cell, proteins are organized in machineries, underlaid by a complex network of interactions. Identifying protein interactions is thus crucial to our understanding of cell functioning. Technical advances in molecular biology and genomic technology now allow for the systematic study of the interactions occurring in a given organism. This review first presents the techniques readily available to microbiologists for studying protein-protein interactions in bacteria, as well as their usability for high-throughput studies. Two types of techniques need to be considered: (1) the isolation of protein complexes from the organism of interest by affinity purification, and subsequent identification of the complex partners by mass spectrometry and (2) two-hybrid techniques, in general based on the production of two recombinant proteins whose interaction has to be tested in a reporter cell. Next, we summarize the bacterial interactomes already published. Finally, the strengths and pitfalls of the techniques are discussed, together with the potential prospect of interactome studies in bacteria.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 6%
Turkey 1 3%
Unknown 32 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 29%
Researcher 9 26%
Student > Postgraduate 3 9%
Student > Bachelor 2 6%
Professor 2 6%
Other 6 17%
Unknown 3 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 43%
Biochemistry, Genetics and Molecular Biology 4 11%
Computer Science 3 9%
Veterinary Science and Veterinary Medicine 1 3%
Social Sciences 1 3%
Other 3 9%
Unknown 8 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 October 2013.
All research outputs
#17,537,548
of 25,711,518 outputs
Outputs from Methods in molecular biology
#6,112
of 14,332 outputs
Outputs of similar age
#174,170
of 251,651 outputs
Outputs of similar age from Methods in molecular biology
#287
of 497 outputs
Altmetric has tracked 25,711,518 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,332 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 41st percentile – i.e., 41% of its peers scored the same or lower than it.
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We're also able to compare this research output to 497 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.