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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Cohort profile: Greifswald approach to individualized medicine (GANI_MED)
|
|---|---|
| Published in |
Journal of Translational Medicine, May 2014
|
| DOI | 10.1186/1479-5876-12-144 |
| Pubmed ID | |
| Authors |
Hans J Grabe, Heinrich Assel, Thomas Bahls, Marcus Dörr, Karlhans Endlich, Nicole Endlich, Pia Erdmann, Ralf Ewert, Stephan B Felix, Beate Fiene, Tobias Fischer, Steffen Flessa, Nele Friedrich, Mariacarla Gadebusch-Bondio, Manuela Gesell Salazar, Elke Hammer, Robin Haring, Christoph Havemann, Michael Hecker, Wolfgang Hoffmann, Birte Holtfreter, Tim Kacprowski, Kathleen Klein, Thomas Kocher, Holger Kock, Janina Krafczyk, Jana Kuhn, Martin Langanke, Uwe Lendeckel, Markus M Lerch, Wolfgang Lieb, Roberto Lorbeer, Julia Mayerle, Konrad Meissner, Henriette Meyer zu Schwabedissen, Matthias Nauck, Konrad Ott, Wolfgang Rathmann, Rainer Rettig, Claudia Richardt, Karen Saljé, Ulf Schminke, Andrea Schulz, Matthias Schwab, Werner Siegmund, Sylvia Stracke, Karsten Suhre, Marius Ueffing, Saskia Ungerer, Uwe Völker, Henry Völzke, Henri Wallaschofski, Vivian Werner, Marek T Zygmunt, Heyo K Kroemer |
| Abstract |
Individualized Medicine aims at providing optimal treatment for an individual patient at a given time based on his specific genetic and molecular characteristics. This requires excellent clinical stratification of patients as well as the availability of genomic data and biomarkers as prerequisites for the development of novel diagnostic tools and therapeutic strategies. The University Medicine Greifswald, Germany, has launched the "Greifswald Approach to Individualized Medicine" (GANI_MED) project to address major challenges of Individualized Medicine. Herein, we describe the implementation of the scientific and clinical infrastructure that allows future translation of findings relevant to Individualized Medicine into clinical practice. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 1% |
| United Kingdom | 1 | 1% |
| Unknown | 74 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 14% |
| Researcher | 10 | 13% |
| Student > Ph. D. Student | 8 | 11% |
| Student > Bachelor | 8 | 11% |
| Professor | 6 | 8% |
| Other | 19 | 25% |
| Unknown | 14 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 21 | 28% |
| Agricultural and Biological Sciences | 7 | 9% |
| Biochemistry, Genetics and Molecular Biology | 7 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 7% |
| Psychology | 5 | 7% |
| Other | 16 | 21% |
| Unknown | 15 | 20% |
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 17 February 2015.
All research outputs
#16,722,190
of 25,374,917 outputs
Outputs from Journal of Translational Medicine
#2,335
of 4,635 outputs
Outputs of similar age
#138,177
of 240,006 outputs
Outputs of similar age from Journal of Translational Medicine
#44
of 97 outputs
Altmetric has tracked 25,374,917 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 4,635 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
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 240,006 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 97 others from the same source and published within six weeks on either side of this one. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.