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Combining ontologies and workflows to design formal protocols for biological laboratories

Overview of attention for article published in Automated Experimentation, January 2010
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1 tweeter

Citations

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5 Dimensions

Readers on

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62 Mendeley
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8 CiteULike
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Title
Combining ontologies and workflows to design formal protocols for biological laboratories
Published in
Automated Experimentation, January 2010
DOI 10.1186/1759-4499-2-3
Pubmed ID
Authors

Alessandro Maccagnan, Mauro Riva, Erika Feltrin, Barbara Simionati, Tullio Vardanega, Giorgio Valle, Nicola Cannata

Abstract

Laboratory protocols in life sciences tend to be written in natural language, with negative consequences on repeatability, distribution and automation of scientific experiments. Formalization of knowledge is becoming popular in science. In the case of laboratory protocols two levels of formalization are needed: one for the entities and individuals operations involved in protocols and another one for the procedures, which can be manually or automatically executed. This study aims to combine ontologies and workflows for protocol formalization.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 3 5%
United States 2 3%
India 1 2%
Sweden 1 2%
United Kingdom 1 2%
New Zealand 1 2%
Netherlands 1 2%
Germany 1 2%
Unknown 51 82%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 27%
Professor > Associate Professor 8 13%
Student > Bachelor 7 11%
Student > Master 7 11%
Professor 6 10%
Other 12 19%
Unknown 5 8%
Readers by discipline Count As %
Computer Science 23 37%
Agricultural and Biological Sciences 13 21%
Engineering 6 10%
Medicine and Dentistry 6 10%
Biochemistry, Genetics and Molecular Biology 5 8%
Other 5 8%
Unknown 4 6%

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 26 November 2014.
All research outputs
#3,552,803
of 5,036,385 outputs
Outputs from Automated Experimentation
#6
of 6 outputs
Outputs of similar age
#116,159
of 172,413 outputs
Outputs of similar age from Automated Experimentation
#1
of 1 outputs
Altmetric has tracked 5,036,385 research outputs across all sources so far. This one is in the 16th percentile – i.e., 16% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.7. This one scored the same or higher as 0 of them.
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 172,413 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them