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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Defining Disease, Diagnosis, and Translational Medicine within a Homeostatic Perturbation Paradigm: The National Institutes of Health Undiagnosed Diseases Program Experience
|
|---|---|
| Published in |
Frontiers in Medicine, May 2017
|
| DOI | 10.3389/fmed.2017.00062 |
| Pubmed ID | |
| Authors |
Timothy Gall, Elise Valkanas, Christofer Bello, Thomas Markello, Christopher Adams, William P. Bone, Alexander J. Brandt, Jennifer M. Brazill, Lynn Carmichael, Mariska Davids, Joie Davis, Zoraida Diaz-Perez, David Draper, Jeremy Elson, Elise D. Flynn, Rena Godfrey, Catherine Groden, Cheng-Kang Hsieh, Roxanne Fischer, Gretchen A. Golas, Jessica Guzman, Yan Huang, Megan S. Kane, Elizabeth Lee, Chong Li, Amanda E. Links, Valerie Maduro, May Christine V. Malicdan, Fayeza S. Malik, Michele Nehrebecky, Joun Park, Paul Pemberton, Katherine Schaffer, Dimitre Simeonov, Murat Sincan, Damian Smedley, Zaheer Valivullah, Colleen Wahl, Nicole Washington, Lynne A. Wolfe, Karen Xu, Yi Zhu, William A. Gahl, Cynthia J. Tifft, Camillo Toro, David R. Adams, Miao He, Peter N. Robinson, Melissa A. Haendel, R. Grace Zhai, Cornelius F. Boerkoel |
| Abstract |
Traditionally, the use of genomic information for personalized medical decisions relies on prior discovery and validation of genotype-phenotype associations. This approach constrains care for patients presenting with undescribed problems. The National Institutes of Health (NIH) Undiagnosed Diseases Program (UDP) hypothesized that defining disease as maladaptation to an ecological niche allows delineation of a logical framework to diagnose and evaluate such patients. Herein, we present the philosophical bases, methodologies, and processes implemented by the NIH UDP. The NIH UDP incorporated use of the Human Phenotype Ontology, developed a genomic alignment strategy cognizant of parental genotypes, pursued agnostic biochemical analyses, implemented functional validation, and established virtual villages of global experts. This systematic approach provided a foundation for the diagnostic or non-diagnostic answers provided to patients and serves as a paradigm for scalable translational research. |
X Demographics
The data shown below were collected from the profiles of 35 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 | 17 | 49% |
| Australia | 2 | 6% |
| United Kingdom | 1 | 3% |
| New Zealand | 1 | 3% |
| Spain | 1 | 3% |
| Switzerland | 1 | 3% |
| Japan | 1 | 3% |
| Unknown | 11 | 31% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 22 | 63% |
| Scientists | 11 | 31% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
| Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 41 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 20% |
| Student > Master | 7 | 17% |
| Other | 4 | 10% |
| Professor | 2 | 5% |
| Student > Bachelor | 2 | 5% |
| Other | 8 | 20% |
| Unknown | 10 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 20% |
| Biochemistry, Genetics and Molecular Biology | 7 | 17% |
| Engineering | 3 | 7% |
| Nursing and Health Professions | 2 | 5% |
| Agricultural and Biological Sciences | 1 | 2% |
| Other | 6 | 15% |
| Unknown | 14 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 30 August 2017.
All research outputs
#1,607,732
of 24,974,461 outputs
Outputs from Frontiers in Medicine
#438
of 6,927 outputs
Outputs of similar age
#30,659
of 319,069 outputs
Outputs of similar age from Frontiers in Medicine
#4
of 55 outputs
Altmetric has tracked 24,974,461 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,927 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.8. 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 319,069 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 55 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 94% of its contemporaries.