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An automated real-time integration and interoperability framework for bioinformatics

Overview of attention for article published in BMC Bioinformatics, October 2015
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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 (83rd percentile)

Mentioned by

twitter
11 tweeters
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
32 Mendeley
citeulike
5 CiteULike
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Title
An automated real-time integration and interoperability framework for bioinformatics
Published in
BMC Bioinformatics, October 2015
DOI 10.1186/s12859-015-0761-3
Pubmed ID
Authors

Pedro Lopes, José Luís Oliveira

Abstract

In recent years data integration has become an everyday undertaking for life sciences researchers. Aggregating and processing data from disparate sources, whether through specific developed software or via manual processes, is a common task for scientists. However, the scope and usability of the majority of current integration tools fail to deal with the fast growing and highly dynamic nature of biomedical data. In this work we introduce a reactive and event-driven framework that simplifies real-time data integration and interoperability. This platform facilitates otherwise difficult tasks, such as connecting heterogeneous services, indexing, linking and transferring data from distinct resources, or subscribing to notifications regarding the timeliness of dynamic data. For developers, the framework automates the deployment of integrative and interoperable bioinformatics applications, using atomic data storage for content change detection, and enabling agent-based intelligent extract, transform and load tasks. This work bridges the gap between the growing number of services, accessing specific data sources or algorithms, and the growing number of users, performing simple integration tasks on a recurring basis, through a streamlined workspace available to researchers and developers alike.

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 3%
United States 1 3%
Brazil 1 3%
Unknown 29 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 28%
Student > Ph. D. Student 8 25%
Student > Bachelor 4 13%
Student > Master 4 13%
Student > Postgraduate 2 6%
Other 4 13%
Unknown 1 3%
Readers by discipline Count As %
Computer Science 10 31%
Biochemistry, Genetics and Molecular Biology 6 19%
Agricultural and Biological Sciences 6 19%
Engineering 3 9%
Business, Management and Accounting 2 6%
Other 2 6%
Unknown 3 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 20 October 2015.
All research outputs
#2,632,248
of 18,899,605 outputs
Outputs from BMC Bioinformatics
#1,028
of 6,462 outputs
Outputs of similar age
#43,595
of 262,732 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 18,899,605 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,462 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done well, scoring higher than 84% 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 262,732 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 83% of its contemporaries.
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