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The tissue microarray data exchange specification: A community-based, open source tool for sharing tissue microarray data

Overview of attention for article published in BMC Medical Informatics and Decision Making, May 2003
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Title
The tissue microarray data exchange specification: A community-based, open source tool for sharing tissue microarray data
Published in
BMC Medical Informatics and Decision Making, May 2003
DOI 10.1186/1472-6947-3-5
Pubmed ID
Authors

Jules J Berman, Mary E Edgerton, Bruce A Friedman

Abstract

Tissue Microarrays (TMAs) allow researchers to examine hundreds of small tissue samples on a single glass slide. The information held in a single TMA slide may easily involve Gigabytes of data. To benefit from TMA technology, the scientific community needs an open source TMA data exchange specification that will convey all of the data in a TMA experiment in a format that is understandable to both humans and computers. A data exchange specification for TMAs allows researchers to submit their data to journals and to public data repositories and to share or merge data from different laboratories. In May 2001, the Association of Pathology Informatics (API) hosted the first in a series of four workshops, co-sponsored by the National Cancer Institute, to develop an open, community-supported TMA data exchange specification.

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 9%
Germany 1 3%
United Kingdom 1 3%
Switzerland 1 3%
Spain 1 3%
Argentina 1 3%
Unknown 24 75%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 22%
Student > Ph. D. Student 6 19%
Professor 3 9%
Other 3 9%
Student > Master 3 9%
Other 6 19%
Unknown 4 13%
Readers by discipline Count As %
Medicine and Dentistry 15 47%
Agricultural and Biological Sciences 4 13%
Computer Science 3 9%
Biochemistry, Genetics and Molecular Biology 2 6%
Sports and Recreations 1 3%
Other 3 9%
Unknown 4 13%
Attention Score in Context

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 13 January 2014.
All research outputs
#18,360,179
of 22,739,983 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,567
of 1,985 outputs
Outputs of similar age
#47,847
of 50,324 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#3
of 4 outputs
Altmetric has tracked 22,739,983 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,985 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 9th percentile – i.e., 9% 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 50,324 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.