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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Systematic evaluation of connectivity map for disease indications
|
|---|---|
| Published in |
Genome Medicine, December 2014
|
| DOI | 10.1186/s13073-014-0095-1 |
| Pubmed ID | |
| Authors |
Jie Cheng, Lun Yang, Vinod Kumar, Pankaj Agarwal |
| Abstract |
Connectivity map data and associated methodologies have become a valuable tool in understanding drug mechanism of action (MOA) and discovering new indications for drugs. One of the key ideas of connectivity map (CMAP) is to measure the connectivity between disease gene expression signatures and compound-induced gene expression profiles. Despite multiple impressive anecdotal validations, only a few systematic evaluations have assessed the accuracy of this aspect of CMAP, and most of these utilize drug-to-drug matching to transfer indications across the two drugs. |
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 % |
|---|---|---|
| United Kingdom | 1 | 25% |
| Unknown | 3 | 75% |
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 124 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 2% |
| France | 1 | <1% |
| Slovenia | 1 | <1% |
| Unknown | 120 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 32 | 26% |
| Researcher | 31 | 25% |
| Student > Doctoral Student | 8 | 6% |
| Student > Bachelor | 7 | 6% |
| Student > Master | 6 | 5% |
| Other | 19 | 15% |
| Unknown | 21 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 30 | 24% |
| Agricultural and Biological Sciences | 19 | 15% |
| Computer Science | 12 | 10% |
| Medicine and Dentistry | 12 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 3% |
| Other | 19 | 15% |
| Unknown | 28 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 23 August 2021.
All research outputs
#2,378,178
of 23,100,534 outputs
Outputs from Genome Medicine
#552
of 1,449 outputs
Outputs of similar age
#35,102
of 363,019 outputs
Outputs of similar age from Genome Medicine
#24
of 69 outputs
Altmetric has tracked 23,100,534 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,449 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.8. This one has gotten more attention than average, scoring higher than 61% 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 363,019 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 69 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 66% of its contemporaries.