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 |
Co-acting gene networks predict TRAIL responsiveness of tumour cells with high accuracy
|
|---|---|
| Published in |
BMC Genomics, December 2014
|
| DOI | 10.1186/1471-2164-15-1144 |
| Pubmed ID | |
| Authors |
Paul O’Reilly, Csaba Ortutay, Grainne Gernon, Enda O’Connell, Cathal Seoighe, Susan Boyce, Luis Serrano, Eva Szegezdi |
| Abstract |
Identification of differentially expressed genes from transcriptomic studies is one of the most common mechanisms to identify tumor biomarkers. This approach however is not well suited to identify interaction between genes whose protein products potentially influence each other, which limits its power to identify molecular wiring of tumour cells dictating response to a drug. Due to the fact that signal transduction pathways are not linear and highly interlinked, the biological response they drive may be better described by the relative amount of their components and their functional relationships than by their individual, absolute expression. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 32% |
| Student > Bachelor | 4 | 14% |
| Student > Master | 4 | 14% |
| Student > Ph. D. Student | 3 | 11% |
| Student > Doctoral Student | 1 | 4% |
| Other | 4 | 14% |
| Unknown | 3 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 14% |
| Engineering | 4 | 14% |
| Agricultural and Biological Sciences | 4 | 14% |
| Computer Science | 4 | 14% |
| Medicine and Dentistry | 2 | 7% |
| Other | 5 | 18% |
| Unknown | 5 | 18% |
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 15 August 2015.
All research outputs
#18,387,239
of 22,775,504 outputs
Outputs from BMC Genomics
#8,171
of 10,642 outputs
Outputs of similar age
#255,848
of 353,125 outputs
Outputs of similar age from BMC Genomics
#187
of 238 outputs
Altmetric has tracked 22,775,504 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,642 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% 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 353,125 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 238 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.