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Clinical proteomics of enervated neurons

Overview of attention for article published in Clinical Proteomics, May 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#11 of 156)
  • High Attention Score compared to outputs of the same age (86th percentile)

Mentioned by

1 news outlet
5 tweeters


2 Dimensions

Readers on

11 Mendeley
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Clinical proteomics of enervated neurons
Published in
Clinical Proteomics, May 2016
DOI 10.1186/s12014-016-9112-2
Pubmed ID

Mohor Biplab Sengupta, Arunabha Chakrabarti, Suparna Saha, Debashis Mukhopadhyay


The dynamic field of neurosciences entails ever increasing search for molecular mechanisms of disease states, especially in the domain of neurodegenerative disorders. The previous century heralded the techniques in proteomics when indexing of the human proteomes relating to various disease conditions became important. Early stage research in certain diseases or pathological conditions requires a more holistic approach of first discovering the proteins of interest for the condition. Despite its limitations, proteomics is one of the most powerful techniques available to us today to dissect the molecular scenario in a particular disease situation. In this review we will discuss about the current clinical research in neurodegenerative disorders that employ proteomics techniques. We will specifically focus on our understanding of Alzheimer's disease, traumatic spinal cord injury and neuromyelitis optica. Discussions will include ongoing worldwide research in these areas, research in India and specifically our laboratory in these domains of neurodegenerative conditions.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 3 27%
Student > Ph. D. Student 2 18%
Student > Bachelor 2 18%
Lecturer > Senior Lecturer 1 9%
Other 1 9%
Other 2 18%
Readers by discipline Count As %
Engineering 3 27%
Biochemistry, Genetics and Molecular Biology 2 18%
Agricultural and Biological Sciences 2 18%
Medicine and Dentistry 1 9%
Nursing and Health Professions 1 9%
Other 2 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 13 May 2016.
All research outputs
of 12,480,234 outputs
Outputs from Clinical Proteomics
of 156 outputs
Outputs of similar age
of 264,156 outputs
Outputs of similar age from Clinical Proteomics
of 3 outputs
Altmetric has tracked 12,480,234 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 156 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done particularly well, scoring higher than 92% 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 264,156 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them