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Integration of Proteomics, Bioinformatics, and Systems Biology in Traumatic Brain Injury Biomarker Discovery

Overview of attention for article published in Frontiers in Neurology, January 2013
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  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

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3 X users

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Title
Integration of Proteomics, Bioinformatics, and Systems Biology in Traumatic Brain Injury Biomarker Discovery
Published in
Frontiers in Neurology, January 2013
DOI 10.3389/fneur.2013.00061
Pubmed ID
Authors

J.D. Guingab-Cagmat, E.B. Cagmat, R.L. Hayes, J. Anagli

Abstract

Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high-throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics, and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform, and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics, and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Israel 1 1%
Colombia 1 1%
Unknown 66 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 17%
Researcher 10 14%
Professor > Associate Professor 9 13%
Student > Master 6 9%
Student > Bachelor 6 9%
Other 11 16%
Unknown 16 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 21%
Medicine and Dentistry 12 17%
Neuroscience 7 10%
Engineering 5 7%
Computer Science 3 4%
Other 11 16%
Unknown 17 24%
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 04 November 2013.
All research outputs
#13,890,585
of 22,711,242 outputs
Outputs from Frontiers in Neurology
#5,423
of 11,620 outputs
Outputs of similar age
#164,380
of 280,736 outputs
Outputs of similar age from Frontiers in Neurology
#52
of 210 outputs
Altmetric has tracked 22,711,242 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,620 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has gotten more attention than average, scoring higher than 51% of its peers.
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 280,736 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 210 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 73% of its contemporaries.