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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Capturing Alzheimer's disease genomes with induced pluripotent stem cells: prospects and challenges
|
|---|---|
| Published in |
Genome Medicine, July 2011
|
| DOI | 10.1186/gm265 |
| Pubmed ID | |
| Authors |
Mason A Israel, Lawrence SB Goldstein |
| Abstract |
A crucial limitation to our understanding of Alzheimer's disease (AD) is the inability to test hypotheses on live, patient-specific neurons. Patient autopsies are limited in supply and only reveal endpoints of disease. Rodent models harboring familial AD mutations lack important pathologies, and animal models have not been useful in modeling the sporadic form of AD because of complex genetics. The recent development of induced pluripotent stem cells (iPSCs) provides a method to create live, patient-specific models of disease and to investigate disease phenotypes in vitro. In this review, we discuss the genetics of AD patients and the potential for iPSCs to capture the genomes of these individuals and generate relevant cell types. Specifically, we examine recent insights into the genetic fidelity of iPSCs, advances in the area of neuronal differentiation, and the ability of iPSCs to model neurodegenerative diseases. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 6% |
| United Kingdom | 1 | 2% |
| Italy | 1 | 2% |
| Unknown | 59 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 26% |
| Student > Ph. D. Student | 13 | 20% |
| Student > Master | 10 | 15% |
| Professor | 7 | 11% |
| Student > Bachelor | 6 | 9% |
| Other | 13 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 36 | 55% |
| Neuroscience | 10 | 15% |
| Medicine and Dentistry | 9 | 14% |
| Biochemistry, Genetics and Molecular Biology | 7 | 11% |
| Psychology | 1 | 2% |
| Other | 2 | 3% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 22 September 2012.
All research outputs
#17,646,807
of 22,651,245 outputs
Outputs from Genome Medicine
#1,348
of 1,431 outputs
Outputs of similar age
#97,414
of 119,557 outputs
Outputs of similar age from Genome Medicine
#5
of 5 outputs
Altmetric has tracked 22,651,245 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,431 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.5. This one is in the 4th percentile – i.e., 4% 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 119,557 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.