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Excel–SBOL Converter: Creating SBOL from Excel Templates and Vice Versa

Overview of attention for article published in ACS Synthetic Biology, January 2023
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Article details
Title
Excel–SBOL Converter: Creating SBOL from Excel Templates and Vice Versa
Published in
ACS Synthetic Biology, January 2023
DOI 10.1021/acssynbio.2c00521
Pubmed ID
Authors
Abstract

Standards support synthetic biology research by enabling the exchange of component information. However, using formal representations, such as the Synthetic Biology Open Language (SBOL), typically requires either a thorough understanding of these standards or a suite of tools developed in concurrence with the ontologies. Since these tools may be a barrier for use by many practitioners, the Excel-SBOL Converter was developed to facilitate the use of SBOL and integration into existing workflows. The converter consists of two Python libraries: one that converts Excel templates to SBOL and another that converts SBOL to an Excel workbook. Both libraries can be used either directly or via a SynBioHub plugin.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 3 11%
Lecturer 1 4%
Student > Doctoral Student 1 4%
Professor 1 4%
Student > Ph. D. Student 1 4%
Other 3 11%
Unknown 17 63%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 7%
Agricultural and Biological Sciences 2 7%
Chemical Engineering 1 4%
Nursing and Health Professions 1 4%
Computer Science 1 4%
Other 2 7%
Unknown 18 67%
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 04 January 2023.
All research outputs
#20,673,680
of 25,392,582 outputs
Outputs from ACS Synthetic Biology
#2,625
of 2,904 outputs
Outputs of similar age
#351,029
of 474,361 outputs
Outputs of similar age from ACS Synthetic Biology
#68
of 79 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,904 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one is in the 6th percentile – i.e., 6% 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 474,361 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.