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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Characterization of a genetic mouse model of lung cancer: a promise to identify Non-Small Cell Lung Cancer therapeutic targets and biomarkers
|
|---|---|
| Published in |
BMC Genomics, May 2014
|
| DOI | 10.1186/1471-2164-15-s3-s1 |
| Pubmed ID | |
| Authors |
Federica Riccardo, Maddalena Arigoni, Genny Buson, Elisa Zago, Manuela Iezzi, Dario Livio Longo, Matteo Carrara, Alessandra Fiore, Simona Nuzzo, Silvio Bicciato, Patrizia Nanni, Lorena Landuzzi, Federica Cavallo, Raffaele Calogero, Elena Quaglino |
| Abstract |
Non-small cell lung cancer (NSCLC) accounts for 81% of all cases of lung cancer and they are often fatal because 60% of the patients are diagnosed at an advanced stage. Besides the need for earlier diagnosis, there is a high need for additional effective therapies. In this work, we investigated the feasibility of a lung cancer progression mouse model, mimicking features of human aggressive NSCLC, as biological reservoir for potential therapeutic targets and biomarkers. |
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 % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 53 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 25% |
| Researcher | 11 | 21% |
| Student > Bachelor | 8 | 15% |
| Other | 4 | 8% |
| Professor | 3 | 6% |
| Other | 4 | 8% |
| Unknown | 10 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 12 | 23% |
| Agricultural and Biological Sciences | 10 | 19% |
| Medicine and Dentistry | 10 | 19% |
| Immunology and Microbiology | 4 | 8% |
| Social Sciences | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 11 | 21% |
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 01 August 2014.
All research outputs
#20,233,547
of 22,759,618 outputs
Outputs from BMC Genomics
#9,263
of 10,637 outputs
Outputs of similar age
#193,292
of 227,401 outputs
Outputs of similar age from BMC Genomics
#159
of 192 outputs
Altmetric has tracked 22,759,618 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,637 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 1st percentile – i.e., 1% 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 227,401 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 192 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.