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Mendeley readers
Attention Score in Context
| Title |
Opportunities and Limitations of Modelling Alzheimer’s Disease with Induced Pluripotent Stem Cells
|
|---|---|
| Published in |
Journal of Clinical Medicine, December 2014
|
| DOI | 10.3390/jcm3041357 |
| Pubmed ID | |
| Authors |
Dmitry A Ovchinnikov, Ernst J Wolvetang |
| Abstract |
Reprogramming of somatic cells into induced pluripotent stem cells (iPSCs) has opened the way for patient-specific disease modelling. Following their differentiation into neuronal cell types, iPSC have enabled the investigation of human neurodegenerative diseases, such as Alzheimer's disease (AD). While human iPSCs certainly provide great opportunities to repeatedly interrogate specific human brain cell types of individuals with familial and sporadic forms of the disease, the complex aetiology and timescale over which AD develops in humans poses particular challenges to iPSC-based AD models. Here, we discuss the current state-of-play in the context of these and other iPSC model-related challenges and elaborate on likely future developments in this field of research. |
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 % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Unknown | 40 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 22% |
| Researcher | 7 | 17% |
| Student > Bachelor | 6 | 15% |
| Student > Doctoral Student | 5 | 12% |
| Student > Master | 5 | 12% |
| Other | 7 | 17% |
| Unknown | 2 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 17 | 41% |
| Biochemistry, Genetics and Molecular Biology | 11 | 27% |
| Neuroscience | 7 | 17% |
| Engineering | 2 | 5% |
| Unknown | 4 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 07 August 2015.
All research outputs
#4,100,069
of 22,774,233 outputs
Outputs from Journal of Clinical Medicine
#1,842
of 11,873 outputs
Outputs of similar age
#58,613
of 359,774 outputs
Outputs of similar age from Journal of Clinical Medicine
#9
of 27 outputs
Altmetric has tracked 22,774,233 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,873 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.1. This one has done well, scoring higher than 84% 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 359,774 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 83% of its contemporaries.
We're also able to compare this research output to 27 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 66% of its contemporaries.