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Genome-wide analysis of regulatory proteases sequences identified through bioinformatics data mining in Taenia solium

Overview of attention for article published in BMC Genomics, June 2014
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Title
Genome-wide analysis of regulatory proteases sequences identified through bioinformatics data mining in Taenia solium
Published in
BMC Genomics, June 2014
DOI 10.1186/1471-2164-15-428
Pubmed ID
Authors

Hong-Bin Yan, Zhong-Zi Lou, Li Li, Paul J Brindley, Yadong Zheng, Xuenong Luo, Junling Hou, Aijiang Guo, Wan-Zhong Jia, Xuepeng Cai

Abstract

Cysticercosis remains a major neglected tropical disease of humanity in many regions, especially in sub-Saharan Africa, Central America and elsewhere. Owing to the emerging drug resistance and the inability of current drugs to prevent re-infection, identification of novel vaccines and chemotherapeutic agents against Taenia solium and related helminth pathogens is a public health priority. The T. solium genome and the predicted proteome were reported recently, providing a wealth of information from which new interventional targets might be identified. In order to characterize and classify the entire repertoire of protease-encoding genes of T. solium, which act fundamental biological roles in all life processes, we analyzed the predicted proteins of this cestode through a combination of bioinformatics tools. Functional annotation was performed to yield insights into the signaling processes relevant to the complex developmental cycle of this tapeworm and to highlight a suite of the proteases as potential intervention targets.

X Demographics

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The data shown below were collected from the profiles of 4 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 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 2%
Unknown 57 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 21%
Student > Ph. D. Student 10 17%
Student > Bachelor 10 17%
Researcher 7 12%
Professor 3 5%
Other 8 14%
Unknown 8 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 19%
Medicine and Dentistry 10 17%
Agricultural and Biological Sciences 10 17%
Nursing and Health Professions 3 5%
Computer Science 3 5%
Other 10 17%
Unknown 11 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 January 2015.
All research outputs
#15,169,543
of 25,373,627 outputs
Outputs from BMC Genomics
#5,391
of 11,244 outputs
Outputs of similar age
#122,523
of 242,197 outputs
Outputs of similar age from BMC Genomics
#118
of 279 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 242,197 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 279 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.