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Mendeley readers
Attention Score in Context
| Title |
Knowledge-based analysis of proteomics data
|
|---|---|
| Published in |
BMC Bioinformatics, November 2012
|
| DOI | 10.1186/1471-2105-13-s16-s13 |
| Pubmed ID | |
| Authors |
Marina Bessarabova, Alexander Ishkin, Lellean JeBailey, Tatiana Nikolskaya, Yuri Nikolsky |
| Abstract |
As it is the case with any OMICs technology, the value of proteomics data is defined by the degree of its functional interpretation in the context of phenotype. Functional analysis of proteomics profiles is inherently complex, as each of hundreds of detected proteins can belong to dozens of pathways, be connected in different context-specific groups by protein interactions and regulated by a variety of one-step and remote regulators. Knowledge-based approach deals with this complexity by creating a structured database of protein interactions, pathways and protein-disease associations from experimental literature and a set of statistical tools to compare the proteomics profiles with this rich source of accumulated knowledge. Here we describe the main methods of ontology enrichment, interactome topology and network analysis applied on a comprehensive, manually curated and semantically consistent knowledge source MetaBase and demonstrate several case studies in different disease areas. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 163 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 1% |
| Colombia | 1 | <1% |
| Netherlands | 1 | <1% |
| Australia | 1 | <1% |
| India | 1 | <1% |
| United Kingdom | 1 | <1% |
| Canada | 1 | <1% |
| China | 1 | <1% |
| Japan | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 152 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 43 | 26% |
| Student > Ph. D. Student | 40 | 25% |
| Student > Master | 14 | 9% |
| Student > Doctoral Student | 13 | 8% |
| Student > Bachelor | 7 | 4% |
| Other | 24 | 15% |
| Unknown | 22 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 56 | 34% |
| Biochemistry, Genetics and Molecular Biology | 40 | 25% |
| Medicine and Dentistry | 11 | 7% |
| Computer Science | 9 | 6% |
| Pharmacology, Toxicology and Pharmaceutical Science | 7 | 4% |
| Other | 12 | 7% |
| Unknown | 28 | 17% |
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 11 December 2012.
All research outputs
#19,897,240
of 24,452,844 outputs
Outputs from BMC Bioinformatics
#6,553
of 7,535 outputs
Outputs of similar age
#144,132
of 187,300 outputs
Outputs of similar age from BMC Bioinformatics
#88
of 110 outputs
Altmetric has tracked 24,452,844 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,535 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 5th percentile – i.e., 5% 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 187,300 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.