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Novel alternative splicing isoform biomarkers identification from high-throughput plasma proteomics profiling of breast cancer

Overview of attention for article published in BMC Systems Biology, December 2013
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Title
Novel alternative splicing isoform biomarkers identification from high-throughput plasma proteomics profiling of breast cancer
Published in
BMC Systems Biology, December 2013
DOI 10.1186/1752-0509-7-s5-s8
Pubmed ID
Authors

Fan Zhang, Mu Wang, Tran Michael, Renee Drabier

Abstract

In the biopharmaceutical industry, biomarkers define molecular taxonomies of patients and diseases and serve as surrogate endpoints in early-phase drug trials. Molecular biomarkers can be much more sensitive than traditional lab tests. Discriminating disease biomarkers by traditional method such as DNA microarray has proved challenging. Alternative splicing isoform represents a new class of diagnostic biomarkers. Recent scientific evidence is demonstrating that the differentiation and quantification of individual alternative splicing isoforms could improve insights into disease diagnosis and management. Identifying and characterizing alternative splicing isoforms are essential to the study of molecular mechanisms and early detection of complex diseases such as breast cancer. However, there are limitations with traditional methods used for alternative splicing isoform determination such as transcriptome-level, low level of coverage and poor focus on alternative splicing.

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The data shown below were collected from the profiles of 2 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 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 3%
Unknown 35 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 36%
Researcher 7 19%
Student > Master 5 14%
Student > Postgraduate 2 6%
Student > Bachelor 2 6%
Other 4 11%
Unknown 3 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 36%
Biochemistry, Genetics and Molecular Biology 8 22%
Computer Science 6 17%
Medicine and Dentistry 2 6%
Immunology and Microbiology 1 3%
Other 2 6%
Unknown 4 11%
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 08 November 2014.
All research outputs
#19,944,091
of 25,373,627 outputs
Outputs from BMC Systems Biology
#777
of 1,132 outputs
Outputs of similar age
#235,560
of 320,288 outputs
Outputs of similar age from BMC Systems Biology
#33
of 46 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.