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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Challenges and opportunities of bovine milk analysis by mass spectrometry
|
|---|---|
| Published in |
Clinical Proteomics, April 2016
|
| DOI | 10.1186/s12014-016-9110-4 |
| Pubmed ID | |
| Authors |
Aparna Verma, Kiran Ambatipudi |
| Abstract |
Bovine milk and its products (e.g. cheese, yoghurt) are an important part of human diet with beneficial effects for all ages. Although analyses of different milk components (e.g. proteins, lipids) pose huge challenges, the use of mass spectrometric (MS)-based techniques is steadily improving our understanding of the complexity of the biological traits that effect milk yield and its components to meet the global demand arising from population growth. In addition, different milk constituents have various applications in veterinary research and medicine, including early disease diagnosis. The aim of the review is to present an overview of the progress made in MS-based analysis of milk, and suggest a multi-pronged MS strategy to better explore different milk components for translational and clinical utilities. |
X Demographics
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 4 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 110 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 14% |
| Researcher | 14 | 13% |
| Student > Master | 12 | 11% |
| Student > Doctoral Student | 8 | 7% |
| Student > Bachelor | 8 | 7% |
| Other | 18 | 16% |
| Unknown | 35 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 28 | 25% |
| Chemistry | 9 | 8% |
| Biochemistry, Genetics and Molecular Biology | 8 | 7% |
| Veterinary Science and Veterinary Medicine | 8 | 7% |
| Immunology and Microbiology | 5 | 5% |
| Other | 13 | 12% |
| Unknown | 39 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 10 May 2017.
All research outputs
#12,892,884
of 22,865,319 outputs
Outputs from Clinical Proteomics
#122
of 285 outputs
Outputs of similar age
#136,706
of 299,207 outputs
Outputs of similar age from Clinical Proteomics
#4
of 6 outputs
Altmetric has tracked 22,865,319 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 285 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has gotten more attention than average, scoring higher than 57% 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 299,207 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.