| Title |
Utilizing protein structure to identify non-random somatic mutations
|
|---|---|
| Published in |
BMC Bioinformatics, June 2013
|
| DOI | 10.1186/1471-2105-14-190 |
| Pubmed ID | |
| Authors |
Gregory A Ryslik, Yuwei Cheng, Kei-Hoi Cheung, Yorgo Modis, Hongyu Zhao |
| Abstract |
Human cancer is caused by the accumulation of somatic mutations in tumor suppressors and oncogenes within the genome. In the case of oncogenes, recent theory suggests that there are only a few key "driver" mutations responsible for tumorigenesis. As there have been significant pharmacological successes in developing drugs that treat cancers that carry these driver mutations, several methods that rely on mutational clustering have been developed to identify them. However, these methods consider proteins as a single strand without taking their spatial structures into account. We propose an extension to current methodology that incorporates protein tertiary structure in order to increase our power when identifying mutation clustering. |
X Demographics
The data shown below were collected from the profiles of 5 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 States | 1 | 20% |
| Norway | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 3% |
| Spain | 2 | 3% |
| United States | 1 | 2% |
| Unknown | 53 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 29% |
| Researcher | 12 | 21% |
| Professor > Associate Professor | 5 | 9% |
| Student > Master | 5 | 9% |
| Student > Bachelor | 4 | 7% |
| Other | 6 | 10% |
| Unknown | 9 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 19 | 33% |
| Computer Science | 11 | 19% |
| Biochemistry, Genetics and Molecular Biology | 8 | 14% |
| Medicine and Dentistry | 6 | 10% |
| Immunology and Microbiology | 2 | 3% |
| Other | 4 | 7% |
| Unknown | 8 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 February 2014.
All research outputs
#12,684,440
of 22,711,645 outputs
Outputs from BMC Bioinformatics
#3,621
of 7,259 outputs
Outputs of similar age
#97,771
of 196,875 outputs
Outputs of similar age from BMC Bioinformatics
#47
of 96 outputs
Altmetric has tracked 22,711,645 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,259 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 48th percentile – i.e., 48% 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 196,875 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 50% of its contemporaries.
We're also able to compare this research output to 96 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 51% of its contemporaries.