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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Detecting recurrent gene mutation in interaction network context using multi-scale graph diffusion
|
|---|---|
| Published in |
BMC Bioinformatics, January 2013
|
| DOI | 10.1186/1471-2105-14-29 |
| Pubmed ID | |
| Authors |
Sepideh Babaei, Marc Hulsman, Marcel Reinders, Jeroen de Ridder |
| Abstract |
Delineating the molecular drivers of cancer, i.e. determining cancer genes and the pathways which they deregulate, is an important challenge in cancer research. In this study, we aim to identify pathways of frequently mutated genes by exploiting their network neighborhood encoded in the protein-protein interaction network. To this end, we introduce a multi-scale diffusion kernel and apply it to a large collection of murine retroviral insertional mutagenesis data. The diffusion strength plays the role of scale parameter, determining the size of the network neighborhood that is taken into account. As a result, in addition to detecting genes with frequent mutations in their genomic vicinity, we find genes that harbor frequent mutations in their interaction network context. |
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 % |
|---|---|---|
| Germany | 1 | 25% |
| Norway | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 1 | 25% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Malaysia | 1 | 1% |
| Germany | 1 | 1% |
| Unknown | 74 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 19 | 25% |
| Researcher | 17 | 22% |
| Student > Master | 10 | 13% |
| Student > Bachelor | 7 | 9% |
| Professor | 4 | 5% |
| Other | 9 | 12% |
| Unknown | 10 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 33% |
| Biochemistry, Genetics and Molecular Biology | 15 | 20% |
| Computer Science | 13 | 17% |
| Medicine and Dentistry | 3 | 4% |
| Engineering | 3 | 4% |
| Other | 6 | 8% |
| Unknown | 11 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 24 January 2013.
All research outputs
#14,102,908
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#4,294
of 7,454 outputs
Outputs of similar age
#163,243
of 285,957 outputs
Outputs of similar age from BMC Bioinformatics
#83
of 145 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,454 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 39th percentile – i.e., 39% 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 285,957 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 145 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.