You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Networking of differentially expressed genes in human cancer cells resistant to methotrexate
|
|---|---|
| Published in |
Genome Medicine, September 2009
|
| DOI | 10.1186/gm83 |
| Pubmed ID | |
| Authors |
Elisabet Selga, Carlota Oleaga, Sara Ramírez, M Cristina de Almagro, Véronique Noé, Carlos J Ciudad |
| Abstract |
The need for an integrated view of data obtained from high-throughput technologies gave rise to network analyses. These are especially useful to rationalize how external perturbations propagate through the expression of genes. To address this issue in the case of drug resistance, we constructed biological association networks of genes differentially expressed in cell lines resistant to methotrexate (MTX). |
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 % |
|---|---|---|
| Spain | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Hungary | 1 | 1% |
| Sweden | 1 | 1% |
| India | 1 | 1% |
| United Kingdom | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 75 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 20% |
| Researcher | 14 | 18% |
| Student > Postgraduate | 8 | 10% |
| Student > Master | 7 | 9% |
| Professor | 6 | 8% |
| Other | 17 | 21% |
| Unknown | 12 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 31 | 39% |
| Biochemistry, Genetics and Molecular Biology | 13 | 16% |
| Chemistry | 5 | 6% |
| Medicine and Dentistry | 4 | 5% |
| Computer Science | 3 | 4% |
| Other | 12 | 15% |
| Unknown | 12 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 08 April 2021.
All research outputs
#8,262,107
of 25,374,647 outputs
Outputs from Genome Medicine
#1,237
of 1,585 outputs
Outputs of similar age
#35,675
of 102,644 outputs
Outputs of similar age from Genome Medicine
#2
of 8 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 1,585 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.8. This one is in the 21st percentile – i.e., 21% 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 102,644 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 64% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.