| Title |
“RADIOTRANSCRIPTOMICS”: A synergy of imaging and transcriptomics in clinical assessment
|
|---|---|
| Published in |
Quantitative Biology, March 2016
|
| DOI | 10.1007/s40484-016-0061-6 |
| Pubmed ID | |
| Authors |
Amal Katrib, William Hsu, Alex Bui, Yi Xing |
| Abstract |
Recent advances in quantitative imaging and "omics" technology have generated a wealth of mineable biological "big data". With the push towards a P4 "predictive, preventive, personalized, and participatory" approach to medicine, researchers began integrating complementary tools to further tune existing diagnostic and therapeutic models. The field of radiogenomics has long pioneered such multidisciplinary investigations in neuroscience and oncology, correlating genotypic and phenotypic signatures to study structural and functional changes in relation to altered molecular behavior. Given the innate dynamic nature of complex disorders and the role of environmental and epigenetic factors in pathogenesis, the transcriptome can further elucidate serial modifications undetected at the genome level. We therefore propose "radiotranscriptomics" as a new member of the P4 medicine initiative, combining transcriptome information, including gene expression and isoform variation, and quantitative image annotations. |
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 | 2 | 40% |
| United Kingdom | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 51 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 25% |
| Researcher | 11 | 22% |
| Student > Bachelor | 8 | 16% |
| Professor > Associate Professor | 3 | 6% |
| Student > Doctoral Student | 2 | 4% |
| Other | 6 | 12% |
| Unknown | 8 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 9 | 18% |
| Agricultural and Biological Sciences | 8 | 16% |
| Medicine and Dentistry | 8 | 16% |
| Computer Science | 7 | 14% |
| Engineering | 4 | 8% |
| Other | 5 | 10% |
| Unknown | 10 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 25 May 2017.
All research outputs
#3,112,335
of 24,833,004 outputs
Outputs from Quantitative Biology
#8
of 89 outputs
Outputs of similar age
#46,950
of 304,332 outputs
Outputs of similar age from Quantitative Biology
#1
of 2 outputs
Altmetric has tracked 24,833,004 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 89 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done particularly well, scoring higher than 91% of its peers.
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We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them