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Robustness analysis on interspecies interaction network for iron and glucose competition between Candida albicans and zebrafish during infection

Overview of attention for article published in BMC Systems Biology, December 2014
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Title
Robustness analysis on interspecies interaction network for iron and glucose competition between Candida albicans and zebrafish during infection
Published in
BMC Systems Biology, December 2014
DOI 10.1186/1752-0509-8-s5-s6
Pubmed ID
Authors

Che Lin, Chin-Nan Lin, Yu-Chao Wang, Fang-Yu Liu, Yu-Wen Chien, Yung-Jen Chuang, Chung-Yu Lan, Wen-Ping Hsieh, Bor-Sen Chen

Abstract

Candida albicans has emerged as an important model organism for the study of infectious disease. Using high-throughput simultaneously quantified time-course transcriptomics, this study constructed host-pathogen interspecies interaction networks between C. albicans and zebrafish during the adhesion, invasion, and damage stages. Given that iron and glucose have been identified as crucial resources required during the infection process between C. albicans and zebrafish, we focused on the construction of the interspecies networks associated with them. Furthermore, a randomization technique was proposed to identify differentially regulated proteins that are statistically eminent for the three infection stages. The behaviors of the highly connected or differentially regulated proteins identified from the resulting networks were further investigated.

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X Demographics

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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 10%
Unknown 19 90%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 24%
Student > Postgraduate 4 19%
Student > Ph. D. Student 4 19%
Researcher 3 14%
Unspecified 1 5%
Other 1 5%
Unknown 3 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 24%
Medicine and Dentistry 3 14%
Immunology and Microbiology 2 10%
Biochemistry, Genetics and Molecular Biology 1 5%
Unspecified 1 5%
Other 4 19%
Unknown 5 24%
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 22 September 2015.
All research outputs
#20,249,662
of 22,778,347 outputs
Outputs from BMC Systems Biology
#1,009
of 1,142 outputs
Outputs of similar age
#298,906
of 356,581 outputs
Outputs of similar age from BMC Systems Biology
#41
of 50 outputs
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