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ArrayExpress update—simplifying data submissions

Overview of attention for article published in Nucleic Acids Research, October 2014
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

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3 X users
wikipedia
4 Wikipedia pages

Citations

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655 Dimensions

Readers on

mendeley
430 Mendeley
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4 CiteULike
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Title
ArrayExpress update—simplifying data submissions
Published in
Nucleic Acids Research, October 2014
DOI 10.1093/nar/gku1057
Pubmed ID
Authors

Nikolay Kolesnikov, Emma Hastings, Maria Keays, Olga Melnichuk, Y. Amy Tang, Eleanor Williams, Miroslaw Dylag, Natalja Kurbatova, Marco Brandizi, Tony Burdett, Karyn Megy, Ekaterina Pilicheva, Gabriella Rustici, Andrew Tikhonov, Helen Parkinson, Robert Petryszak, Ugis Sarkans, Alvis Brazma

Abstract

The ArrayExpress Archive of Functional Genomics Data (http://www.ebi.ac.uk/arrayexpress) is an international functional genomics database at the European Bioinformatics Institute (EMBL-EBI) recommended by most journals as a repository for data supporting peer-reviewed publications. It contains data from over 7000 public sequencing and 42 000 array-based studies comprising over 1.5 million assays in total. The proportion of sequencing-based submissions has grown significantly over the last few years and has doubled in the last 18 months, whilst the rate of microarray submissions is growing slightly. All data in ArrayExpress are available in the MAGE-TAB format, which allows robust linking to data analysis and visualization tools and standardized analysis. The main development over the last two years has been the release of a new data submission tool Annotare, which has reduced the average submission time almost 3-fold. In the near future, Annotare will become the only submission route into ArrayExpress, alongside MAGE-TAB format-based pipelines. ArrayExpress is a stable and highly accessed resource. Our future tasks include automation of data flows and further integration with other EMBL-EBI resources for the representation of multi-omics data.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 430 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 4 <1%
Netherlands 3 <1%
United States 3 <1%
Brazil 2 <1%
Mexico 2 <1%
Australia 1 <1%
Portugal 1 <1%
United Kingdom 1 <1%
India 1 <1%
Other 5 1%
Unknown 407 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 107 25%
Researcher 86 20%
Student > Master 68 16%
Student > Bachelor 43 10%
Student > Doctoral Student 26 6%
Other 51 12%
Unknown 49 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 148 34%
Biochemistry, Genetics and Molecular Biology 100 23%
Computer Science 40 9%
Medicine and Dentistry 19 4%
Engineering 14 3%
Other 41 10%
Unknown 68 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 May 2023.
All research outputs
#7,455,082
of 26,017,215 outputs
Outputs from Nucleic Acids Research
#12,377
of 27,863 outputs
Outputs of similar age
#77,040
of 278,732 outputs
Outputs of similar age from Nucleic Acids Research
#167
of 421 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 27,863 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has gotten more attention than average, scoring higher than 54% 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 278,732 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 421 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 58% of its contemporaries.