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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MOLGENIS/connect: a system for semi-automatic integration of heterogeneous phenotype data with applications in biobanks
|
|---|---|
| Published in |
Bioinformatics, March 2016
|
| DOI | 10.1093/bioinformatics/btw155 |
| Pubmed ID | |
| Authors |
Chao Pang, David van Enckevort, Mark de Haan, Fleur Kelpin, Jonathan Jetten, Dennis Hendriksen, Tommy de Boer, Bart Charbon, Erwin Winder, K Joeri van der Velde, Dany Doiron, Isabel Fortier, Hans Hillege, Morris A Swertz |
| Abstract |
While the size and number of biobanks, patient registries and other data collections are increasing, biomedical researchers still often need to pool data for statistical power, a task that requires time-intensive retrospective integration. To address this challenge, we developed MOLGENIS/connect, a semi-automatic system to find, match and pool data from different sources. The system shortlists relevant source attributes from thousands of candidates using ontology-based query expansion to overcome variations in terminology. Then it generates algorithms that transform source attributes to a common target DataSchema. These include unit conversion, categorical value matching and complex conversion patterns (e.g. calculation of BMI). In comparison to human-experts, MOLGENIS/connect was able to auto-generate 27% of the algorithms perfectly, with an additional 46% needing only minor editing, representing a reduction in the human effort and expertise needed to pool data. Source code, binaries and documentation are available as open-source under LGPLv3 from http://github.com/molgenis/molgenis and www.molgenis.org/connect CONTACT: : [email protected] information: Supplementary data are available at Bioinformatics online. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 3% |
| Brazil | 1 | 3% |
| Unknown | 33 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 34% |
| Student > Ph. D. Student | 12 | 34% |
| Student > Bachelor | 3 | 9% |
| Student > Master | 3 | 9% |
| Student > Doctoral Student | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 3 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 31% |
| Computer Science | 8 | 23% |
| Social Sciences | 3 | 9% |
| Engineering | 3 | 9% |
| Biochemistry, Genetics and Molecular Biology | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 5 | 14% |
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 08 July 2016.
All research outputs
#17,286,645
of 25,374,917 outputs
Outputs from Bioinformatics
#10,569
of 12,809 outputs
Outputs of similar age
#191,982
of 313,631 outputs
Outputs of similar age from Bioinformatics
#166
of 183 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,809 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 11th percentile – i.e., 11% 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 313,631 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 183 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.