| Title |
Identifiability in biobanks: models, measures, and mitigation strategies
|
|---|---|
| Published in |
Human Genetics, July 2011
|
| DOI | 10.1007/s00439-011-1042-5 |
| Pubmed ID | |
| Authors |
Bradley Malin, Grigorios Loukides, Kathleen Benitez, Ellen Wright Clayton |
| Abstract |
The collection and sharing of person-specific biospecimens has raised significant questions regarding privacy. In particular, the question of identifiability, or the degree to which materials stored in biobanks can be linked to the name of the individuals from which they were derived, is under scrutiny. The goal of this paper is to review the extent to which biospecimens and affiliated data can be designated as identifiable. To achieve this goal, we summarize recent research in identifiability assessment for DNA sequence data, as well as associated demographic and clinical data, shared via biobanks. We demonstrate the variability of the degree of risk, the factors that contribute to this variation, and potential ways to mitigate and manage such risk. Finally, we discuss the policy implications of these findings, particularly as they pertain to biobank security and access policies. We situate our review in the context of real data sharing scenarios and biorepositories. |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 5% |
| Germany | 2 | 3% |
| Netherlands | 1 | 1% |
| Iceland | 1 | 1% |
| United Kingdom | 1 | 1% |
| Belgium | 1 | 1% |
| Luxembourg | 1 | 1% |
| Unknown | 63 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 22 | 30% |
| Student > Ph. D. Student | 15 | 20% |
| Other | 5 | 7% |
| Student > Master | 5 | 7% |
| Professor > Associate Professor | 4 | 5% |
| Other | 10 | 14% |
| Unknown | 13 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 17 | 23% |
| Computer Science | 13 | 18% |
| Social Sciences | 8 | 11% |
| Agricultural and Biological Sciences | 7 | 9% |
| Engineering | 3 | 4% |
| Other | 12 | 16% |
| Unknown | 14 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 08 June 2017.
All research outputs
#4,697,128
of 22,790,780 outputs
Outputs from Human Genetics
#467
of 2,953 outputs
Outputs of similar age
#24,861
of 116,398 outputs
Outputs of similar age from Human Genetics
#12
of 34 outputs
Altmetric has tracked 22,790,780 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,953 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has done well, scoring higher than 76% 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 116,398 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 34 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 61% of its contemporaries.