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Comparison of transcriptome technologies in the pathogenic fungus Aspergillus fumigatus reveals novel insights into the genome and MpkA dependent gene expression

Overview of attention for article published in BMC Genomics, October 2012
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Title
Comparison of transcriptome technologies in the pathogenic fungus Aspergillus fumigatus reveals novel insights into the genome and MpkA dependent gene expression
Published in
BMC Genomics, October 2012
DOI 10.1186/1471-2164-13-519
Pubmed ID
Authors

Sebastian Müller, Clara Baldin, Marco Groth, Reinhard Guthke, Olaf Kniemeyer, Axel A Brakhage, Vito Valiante

Abstract

The filamentous fungus Aspergillus fumigatus has become the most important airborne fungal pathogen causing life-threatening infections in immuno-compromised patients. Recently developed high-throughput transcriptome and proteome technologies, such as microarrays, RNA deep-sequencing, and LC-MS/MS of peptide mixtures, are of enormous value for systematically investigating pathogenic organisms. In the field of infection biology, one of the priorities is to collect and standardise data, in order to generate datasets that can be used to investigate and compare pathways and gene responses involved in pathogenicity. The "omics" era provides a multitude of inputs that need to be integrated and assessed. We therefore evaluated the potential of paired-end mRNA-Seq for investigating the regulatory role of the central mitogen activated protein kinase (MpkA). This kinase is involved in the cell wall integrity signalling pathway of A. fumigatus and essential for maintaining an intact cell wall in response to stress.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Chile 1 1%
Unknown 74 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 23%
Student > Ph. D. Student 18 23%
Student > Bachelor 10 13%
Student > Master 9 12%
Professor > Associate Professor 5 6%
Other 12 16%
Unknown 5 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 49%
Biochemistry, Genetics and Molecular Biology 12 16%
Immunology and Microbiology 5 6%
Engineering 3 4%
Computer Science 2 3%
Other 7 9%
Unknown 10 13%
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 02 October 2012.
All research outputs
#20,167,959
of 22,679,690 outputs
Outputs from BMC Genomics
#9,239
of 10,613 outputs
Outputs of similar age
#153,228
of 172,325 outputs
Outputs of similar age from BMC Genomics
#119
of 130 outputs
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