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The Dawning Era of Comprehensive Transcriptome Analysis in Cellular Microbiology

Overview of attention for article published in Frontiers in Microbiology, January 2010
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Title
The Dawning Era of Comprehensive Transcriptome Analysis in Cellular Microbiology
Published in
Frontiers in Microbiology, January 2010
DOI 10.3389/fmicb.2010.00118
Pubmed ID
Authors

Chihiro Aikawa, Fumito Maruyama, Ichiro Nakagawa

Abstract

Bacteria rapidly change their transcriptional patterns during infection in order to adapt to the host environment. To investigate host-bacteria interactions, various strategies including the use of animal infection models, in vitro assay systems and microscopic observations have been used. However, these studies primarily focused on a few specific genes and molecules in bacteria. High-density tiling arrays and massively parallel sequencing analyses are rapidly improving our understanding of the complex host-bacterial interactions through identification and characterization of bacterial transcriptomes. Information resulting from these high-throughput techniques will continue to provide novel information on the complexity, plasticity, and regulation of bacterial transcriptomes as well as their adaptive responses relative to pathogenecity. Here we summarize recent studies using these new technologies and discuss the utility of transcriptome analysis.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Unknown 31 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 31%
Student > Ph. D. Student 6 19%
Student > Bachelor 5 16%
Student > Postgraduate 2 6%
Student > Master 2 6%
Other 3 9%
Unknown 4 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 47%
Environmental Science 3 9%
Medicine and Dentistry 3 9%
Biochemistry, Genetics and Molecular Biology 2 6%
Immunology and Microbiology 2 6%
Other 3 9%
Unknown 4 13%