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X Demographics
Mendeley readers
Attention Score in Context
| Title |
G-DOC Plus – an integrative bioinformatics platform for precision medicine
|
|---|---|
| Published in |
BMC Bioinformatics, April 2016
|
| DOI | 10.1186/s12859-016-1010-0 |
| Pubmed ID | |
| Authors |
Krithika Bhuvaneshwar, Anas Belouali, Varun Singh, Robert M. Johnson, Lei Song, Adil Alaoui, Michael A. Harris, Robert Clarke, Louis M. Weiner, Yuriy Gusev, Subha Madhavan |
| Abstract |
G-DOC Plus is a data integration and bioinformatics platform that uses cloud computing and other advanced computational tools to handle a variety of biomedical BIG DATA including gene expression arrays, NGS and medical images so that they can be analyzed in the full context of other omics and clinical information. G-DOC Plus currently holds data from over 10,000 patients selected from private and public resources including Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the recently added datasets from REpository for Molecular BRAin Neoplasia DaTa (REMBRANDT), caArray studies of lung and colon cancer, ImmPort and the 1000 genomes data sets. The system allows researchers to explore clinical-omic data one sample at a time, as a cohort of samples; or at the level of population, providing the user with a comprehensive view of the data. G-DOC Plus tools have been leveraged in cancer and non-cancer studies for hypothesis generation and validation; biomarker discovery and multi-omics analysis, to explore somatic mutations and cancer MRI images; as well as for training and graduate education in bioinformatics, data and computational sciences. Several of these use cases are described in this paper to demonstrate its multifaceted usability. G-DOC Plus can be used to support a variety of user groups in multiple domains to enable hypothesis generation for precision medicine research. The long-term vision of G-DOC Plus is to extend this translational bioinformatics platform to stay current with emerging omics technologies and analysis methods to continue supporting novel hypothesis generation, analysis and validation for integrative biomedical research. By integrating several aspects of the disease and exposing various data elements, such as outpatient lab workup, pathology, radiology, current treatments, molecular signatures and expected outcomes over a web interface, G-DOC Plus will continue to strengthen precision medicine research. G-DOC Plus is available at: https://gdoc.georgetown.edu . |
X Demographics
The data shown below were collected from the profiles of 26 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 | 8 | 31% |
| Montenegro | 1 | 4% |
| Portugal | 1 | 4% |
| Greece | 1 | 4% |
| Unknown | 15 | 58% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 54% |
| Scientists | 12 | 46% |
Mendeley readers
The data shown below were compiled from readership statistics for 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 1 | <1% |
| Argentina | 1 | <1% |
| Unknown | 109 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 26 | 23% |
| Student > Ph. D. Student | 13 | 12% |
| Student > Master | 13 | 12% |
| Student > Bachelor | 10 | 9% |
| Professor > Associate Professor | 7 | 6% |
| Other | 22 | 20% |
| Unknown | 20 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 19 | 17% |
| Computer Science | 17 | 15% |
| Biochemistry, Genetics and Molecular Biology | 16 | 14% |
| Medicine and Dentistry | 14 | 13% |
| Engineering | 9 | 8% |
| Other | 10 | 9% |
| Unknown | 26 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 11 October 2016.
All research outputs
#2,066,991
of 24,417,958 outputs
Outputs from BMC Bioinformatics
#490
of 7,530 outputs
Outputs of similar age
#33,565
of 303,062 outputs
Outputs of similar age from BMC Bioinformatics
#8
of 103 outputs
Altmetric has tracked 24,417,958 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,530 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 93% of its peers.
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 303,062 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.