| Title |
DriverDBv2: a database for human cancer driver gene research
|
|---|---|
| Published in |
Nucleic Acids Research, December 2015
|
| DOI | 10.1093/nar/gkv1314 |
| Pubmed ID | |
| Authors |
I-Fang Chung, Chen-Yang Chen, Shih-Chieh Su, Chia-Yang Li, Kou-Juey Wu, Hsei-Wei Wang, Wei-Chung Cheng |
| Abstract |
We previously presented DriverDB, a database that incorporates ∼6000 cases of exome-seq data, in addition to annotation databases and published bioinformatics algorithms dedicated to driver gene/mutation identification. The database provides two points of view, 'Cancer' and 'Gene', to help researchers visualize the relationships between cancers and driver genes/mutations. In the updated DriverDBv2 database (http://ngs.ym.edu.tw/driverdb) presented herein, we incorporated >9500 cancer-related RNA-seq datasets and >7000 more exome-seq datasets from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and published papers. Seven additional computational algorithms (meaning that the updated database contains 15 in total), which were developed for driver gene identification, are incorporated into our analysis pipeline, and the results are provided in the 'Cancer' section. Furthermore, there are two main new features, 'Expression' and 'Hotspot', in the 'Gene' section. 'Expression' displays two expression profiles of a gene in terms of sample types and mutation types, respectively. 'Hotspot' indicates the hotspot mutation regions of a gene according to the results provided by four bioinformatics tools. A new function, 'Gene Set', allows users to investigate the relationships among mutations, expression levels and clinical data for a set of genes, a specific dataset and clinical features. |
X Demographics
The data shown below were collected from the profiles of 32 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 | 12 | 38% |
| United Kingdom | 2 | 6% |
| India | 2 | 6% |
| China | 1 | 3% |
| Brazil | 1 | 3% |
| Canada | 1 | 3% |
| Spain | 1 | 3% |
| Belgium | 1 | 3% |
| Japan | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 7 | 22% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 17 | 53% |
| Scientists | 14 | 44% |
| Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Denmark | 2 | 2% |
| Canada | 1 | 1% |
| Finland | 1 | 1% |
| Belgium | 1 | 1% |
| Japan | 1 | 1% |
| Unknown | 88 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 26 | 28% |
| Student > Ph. D. Student | 20 | 21% |
| Student > Master | 11 | 12% |
| Student > Doctoral Student | 5 | 5% |
| Other | 5 | 5% |
| Other | 15 | 16% |
| Unknown | 12 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 33 | 35% |
| Biochemistry, Genetics and Molecular Biology | 25 | 27% |
| Computer Science | 4 | 4% |
| Medicine and Dentistry | 4 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 2% |
| Other | 11 | 12% |
| Unknown | 15 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 35. 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 04 February 2016.
All research outputs
#1,030,792
of 23,607,611 outputs
Outputs from Nucleic Acids Research
#579
of 26,688 outputs
Outputs of similar age
#18,551
of 390,657 outputs
Outputs of similar age from Nucleic Acids Research
#16
of 388 outputs
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