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Microbial Systems Biology

Overview of attention for book
Cover of 'Microbial Systems Biology'

Table of Contents

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    Book Overview
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    Chapter 1 Flow cytometry in environmental microbiology: a rapid approach for the isolation of single cells for advanced molecular biology analysis.
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    Chapter 2 Pressure Cycling Technology in Systems Biology
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    Chapter 3 Targeted Isolation of Proteins from Natural Microbial Communities Living in an Extreme Environment
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    Chapter 4 Bacterial Identification and Subtyping Using DNA Microarray and DNA Sequencing
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    Chapter 5 Microbial Systems Biology
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    Chapter 6 Genome-Wide Mapping of the Binding Sites of Proteins That Interact with DNA
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    Chapter 7 Microbial Proteomics Using Mass Spectrometry
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    Chapter 8 Fourier Transform Infrared Spectroscopy for Molecular Analysis of Microbial Cells
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    Chapter 9 Mass Spectrometry-Based Microbial Metabolomics
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    Chapter 10 Fast Sampling of the Cellular Metabolome
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    Chapter 11 Microbial Systems Biology
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    Chapter 12 Biolog phenotype microarrays.
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    Chapter 13 NanoSIP: NanoSIMS Applications for Microbial Biology
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    Chapter 14 Electrophysiological-Metabolic Modeling of Microbes: Applications in Fuel Cells and Environment Analysis
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    Chapter 15 Simulating Microbial Systems: Addressing Model Uncertainty/Incompleteness via Multiscale and Entropy Methods
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    Chapter 16 Bacterial Genome Annotation
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    Chapter 17 Microbial Systems Biology
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    Chapter 18 Development of Constraint-Based System-Level Models of Microbial Metabolism
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    Chapter 19 Complex Network Analysis in Microbial Systems: Theory and Examples
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    Chapter 20 Modeling a minimal cell.
Attention for Chapter 12: Biolog phenotype microarrays.
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Chapter title
Biolog phenotype microarrays.
Chapter number 12
Book title
Microbial Systems Biology
Published in
Methods in molecular biology, January 2012
DOI 10.1007/978-1-61779-827-6_12
Pubmed ID
Book ISBNs
978-1-61779-826-9, 978-1-61779-827-6
Authors

April Shea, Mark Wolcott, Simon Daefler, David A Rozak, David A. Rozak, Shea, April, Wolcott, Mark, Daefler, Simon, Rozak, David A.

Abstract

Phenotype microarrays nicely complement traditional genomic, transcriptomic, and proteomic analysis by offering opportunities for researchers to ground microbial systems analysis and modeling in a broad yet quantitative assessment of the organism's physiological response to different metabolites and environments. Biolog phenotype assays achieve this by coupling tetrazolium dyes with minimally defined nutrients to measure the impact of hundreds of carbon, nitrogen, phosphorous, and sulfur sources on redox reactions that result from compound-induced effects on the electron transport chain. Over the years, we have used Biolog's reproducible and highly sensitive assays to distinguish closely related bacterial isolates, to understand their metabolic differences, and to model their metabolic behavior using flux balance analysis. This chapter describes Biolog phenotype microarray system components, reagents, and methods, particularly as they apply to bacterial identification, characterization, and metabolic analysis.

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The data shown below were collected from the profile of 1 X user 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 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 <1%
United States 1 <1%
Denmark 1 <1%
Unknown 105 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 21%
Researcher 18 17%
Student > Bachelor 17 16%
Student > Master 12 11%
Student > Doctoral Student 6 6%
Other 13 12%
Unknown 19 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 28 26%
Agricultural and Biological Sciences 25 23%
Immunology and Microbiology 12 11%
Medicine and Dentistry 4 4%
Environmental Science 3 3%
Other 13 12%
Unknown 23 21%
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 06 November 2013.
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#18,353,475
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Outputs from Methods in molecular biology
#7,859
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#196,082
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Outputs of similar age from Methods in molecular biology
#325
of 473 outputs
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