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SeedUSoon: A New Software Program to Improve Seed Stock Management and Plant Line Exchanges between Research Laboratories

Overview of attention for article published in Frontiers in Plant Science, January 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

blogs
1 blog
twitter
4 X users
facebook
1 Facebook page

Citations

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5 Dimensions

Readers on

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26 Mendeley
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Title
SeedUSoon: A New Software Program to Improve Seed Stock Management and Plant Line Exchanges between Research Laboratories
Published in
Frontiers in Plant Science, January 2017
DOI 10.3389/fpls.2017.00013
Pubmed ID
Authors

Céline Charavay, Stéphane Segard, Nathalie Pochon, Laurent Nussaume, Hélène Javot

Abstract

Plant research is supported by an ever-growing collection of mutant or transgenic lines. In the past, a typical basic research laboratory would focus on only a few plant lines that were carefully isolated from collections of lines containing random mutations. The subsequent technological breakthrough in high-throughput sequencing, combined with novel and highly efficient mutagenesis techniques (including site-directed mutagenesis), has led to a recent exponential growth in plant line collections used by individual researchers. Tracking the generation and genetic properties of these genetic resources is thus becoming increasingly challenging for researchers. Another difficulty for researchers is controlling the use of seeds protected by a Material Transfer Agreement, as often only the original recipient of the seeds is aware of the existence of such documents. This situation can thus lead to difficult legal situations. Simultaneously, various institutions and the general public now demand more information about the use of genetically modified organisms (GMOs). In response, researchers are seeking new database solutions to address the triple challenge of research competition, legal constraints, and institutional/public demands. To help plant biology laboratories organize, describe, store, trace, and distribute their seeds, we have developed the new program SeedUSoon, with simplicity in mind. This software contains data management functions that allow the separate tracking of distinct mutations, even in successive crossings or mutagenesis. SeedUSoon reflects the biotechnological diversity of mutations and transgenes contained in any specific line, and the history of their inheritance. It can facilitate GMO certification procedures by distinguishing mutations on the basis of the presence/absence of a transgene, and by recording the technology used for their generation. Its interface can be customized to match the context and rules of any laboratory. In addition, SeedUSoon includes functions to help the laboratory protect intellectual property, export data, and facilitate seed exchange between laboratories. The SeedUSoon program, which is customizable to match individual practices and preferences, provides a powerful toolkit to plant laboratories searching for innovative approaches in laboratory management.

X Demographics

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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 19%
Student > Bachelor 3 12%
Student > Master 3 12%
Professor 2 8%
Other 1 4%
Other 4 15%
Unknown 8 31%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 27%
Computer Science 3 12%
Social Sciences 2 8%
Engineering 2 8%
Business, Management and Accounting 1 4%
Other 2 8%
Unknown 9 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 01 February 2018.
All research outputs
#2,890,575
of 22,947,506 outputs
Outputs from Frontiers in Plant Science
#1,424
of 20,366 outputs
Outputs of similar age
#61,447
of 417,402 outputs
Outputs of similar age from Frontiers in Plant Science
#36
of 517 outputs
Altmetric has tracked 22,947,506 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 20,366 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done particularly well, scoring higher than 93% 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 417,402 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 517 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.