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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Understanding Physiology in the Continuum: Integration of Information from Multiple -Omics Levels
|
|---|---|
| Published in |
Frontiers in Pharmacology, February 2017
|
| DOI | 10.3389/fphar.2017.00091 |
| Pubmed ID | |
| Authors |
Kubra Kamisoglu, Alison Acevedo, Richard R. Almon, Susette Coyle, Siobhan Corbett, Debra C. Dubois, Tung T. Nguyen, William J. Jusko, Ioannis P. Androulakis |
| Abstract |
In this paper, we discuss approaches for integrating biological information reflecting diverse physiologic levels. In particular, we explore statistical and model-based methods for integrating transcriptomic, proteomic and metabolomics data. Our case studies reflect responses to a systemic inflammatory stimulus and in response to an anti-inflammatory treatment. Our paper serves partly as a review of existing methods and partly as a means to demonstrate, using case studies related to human endotoxemia and response to methylprednisolone (MPL) treatment, how specific questions may require specific methods, thus emphasizing the non-uniqueness of the approaches. Finally, we explore novel ways for integrating -omics information with PKPD models, toward the development of more integrated pharmacology models. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 2% |
| Unknown | 43 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 30% |
| Other | 6 | 14% |
| Student > Doctoral Student | 4 | 9% |
| Professor > Associate Professor | 3 | 7% |
| Student > Bachelor | 2 | 5% |
| Other | 8 | 18% |
| Unknown | 8 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 9% |
| Engineering | 4 | 9% |
| Biochemistry, Genetics and Molecular Biology | 4 | 9% |
| Agricultural and Biological Sciences | 4 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 7% |
| Other | 7 | 16% |
| Unknown | 18 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 03 March 2017.
All research outputs
#15,397,332
of 22,957,478 outputs
Outputs from Frontiers in Pharmacology
#6,341
of 16,230 outputs
Outputs of similar age
#197,391
of 312,054 outputs
Outputs of similar age from Frontiers in Pharmacology
#88
of 196 outputs
Altmetric has tracked 22,957,478 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 16,230 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 60% 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 312,054 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 196 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 53% of its contemporaries.