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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Privacy Challenges of Genomic Big Data
|
|---|---|
| Chapter number | 8 |
| Book title |
Healthcare and Big Data Management
|
| Published in |
Advances in experimental medicine and biology, January 2017
|
| DOI | 10.1007/978-981-10-6041-0_8 |
| Pubmed ID | |
| Book ISBNs |
978-9-81-106040-3, 978-9-81-106041-0
|
| Authors |
Hong Shen, Jian Ma |
| Abstract |
With the rapid advancement of high-throughput DNA sequencing technologies, genomics has become a big data discipline where large-scale genetic information of human individuals can be obtained efficiently with low cost. However, such massive amount of personal genomic data creates tremendous challenge for privacy, especially given the emergence of direct-to-consumer (DTC) industry that provides genetic testing services. Here we review the recent development in genomic big data and its implications on privacy. We also discuss the current dilemmas and future challenges of genomic privacy. |
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 % |
|---|---|---|
| France | 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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 38 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 7 | 18% |
| Student > Master | 4 | 11% |
| Student > Doctoral Student | 3 | 8% |
| Researcher | 3 | 8% |
| Student > Ph. D. Student | 3 | 8% |
| Other | 4 | 11% |
| Unknown | 14 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 18% |
| Biochemistry, Genetics and Molecular Biology | 4 | 11% |
| Computer Science | 2 | 5% |
| Agricultural and Biological Sciences | 2 | 5% |
| Social Sciences | 2 | 5% |
| Other | 5 | 13% |
| Unknown | 16 | 42% |
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 24 October 2017.
All research outputs
#20,450,513
of 23,006,268 outputs
Outputs from Advances in experimental medicine and biology
#3,986
of 4,961 outputs
Outputs of similar age
#356,176
of 421,241 outputs
Outputs of similar age from Advances in experimental medicine and biology
#414
of 490 outputs
Altmetric has tracked 23,006,268 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,961 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 1st percentile – i.e., 1% 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 421,241 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 490 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.