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Synthetic Biology

Overview of attention for book
Attention for Chapter: Bio-Algorithmic Workflows for Standardized Synthetic Biology Constructs
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Citations

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Chapter title
Bio-Algorithmic Workflows for Standardized Synthetic Biology Constructs
Book title
Synthetic Biology
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7795-6_20
Pubmed ID
Book ISBNs
978-1-4939-7794-9, 978-1-4939-7795-6
Authors

Goñi-Moreno, Angel, de Lorenzo, Víctor, Angel Goñi-Moreno, Víctor de Lorenzo

Abstract

A synthetic biology workflow covers the roadmap from conceptualization of a genetic device to its construction and measurement. It is composed of databases that provide DNA parts/plasmids, wet-lab methods , software tools to design circuits, simulation packages , and tools to analyze circuit performance. The interdisciplinary nature of such a workflow requires that experimental results and their in-silico counterparts proceed alongside, with constant feedback between them. We present an end-to-end use case for engineering a simple synthetic device, where information standards maintain coherence throughout the workflow. These are the Standard European Vector Architecture (SEVA), the Synthetic Biology Open Language (SBOL), and the Systems Biology Markup Language (SBML).

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X Demographics

The data shown below were collected from the profiles of 4 X users 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 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 38%
Student > Ph. D. Student 4 25%
Student > Bachelor 1 6%
Other 1 6%
Student > Doctoral Student 1 6%
Other 1 6%
Unknown 2 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 25%
Agricultural and Biological Sciences 4 25%
Engineering 2 13%
Business, Management and Accounting 1 6%
Mathematics 1 6%
Other 2 13%
Unknown 2 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 05 February 2019.
All research outputs
#16,022,830
of 25,791,495 outputs
Outputs from Methods in molecular biology
#4,585
of 14,356 outputs
Outputs of similar age
#250,535
of 452,278 outputs
Outputs of similar age from Methods in molecular biology
#412
of 1,486 outputs
Altmetric has tracked 25,791,495 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,356 research outputs from this source. They receive a mean Attention Score of 3.5. This one has gotten more attention than average, scoring higher than 66% of its peers.
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 452,278 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,486 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.