| Title |
A spatial simulation approach to account for protein structure when identifying non-random somatic mutations
|
|---|---|
| Published in |
BMC Bioinformatics, July 2014
|
| DOI | 10.1186/1471-2105-15-231 |
| Pubmed ID | |
| Authors |
Gregory A Ryslik, Yuwei Cheng, Kei-Hoi Cheung, Robert D Bjornson, Daniel Zelterman, Yorgo Modis, Hongyu Zhao |
| Abstract |
Current research suggests that a small set of "driver" mutations are responsible for tumorigenesis while a larger body of "passenger" mutations occur in the tumor but do not progress the disease. Due to recent pharmacological successes in treating cancers caused by driver mutations, a variety of methodologies that attempt to identify such mutations have been developed. Based on the hypothesis that driver mutations tend to cluster in key regions of the protein, the development of cluster identification algorithms has become critical. |
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 % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 6% |
| Korea, Republic of | 1 | 2% |
| Spain | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 41 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 28% |
| Student > Master | 7 | 15% |
| Researcher | 6 | 13% |
| Student > Bachelor | 4 | 9% |
| Student > Doctoral Student | 3 | 6% |
| Other | 6 | 13% |
| Unknown | 8 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 23% |
| Biochemistry, Genetics and Molecular Biology | 9 | 19% |
| Computer Science | 9 | 19% |
| Engineering | 2 | 4% |
| Medicine and Dentistry | 2 | 4% |
| Other | 5 | 11% |
| Unknown | 9 | 19% |
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 22 October 2014.
All research outputs
#18,381,794
of 22,768,097 outputs
Outputs from BMC Bioinformatics
#6,307
of 7,273 outputs
Outputs of similar age
#163,335
of 227,681 outputs
Outputs of similar age from BMC Bioinformatics
#114
of 146 outputs
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