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HSA: A Heuristic Splice Alignment Tool

Overview of attention for article published in BMC Systems Biology, December 2013
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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)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

twitter
8 tweeters
patent
1 patent

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
15 Mendeley
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Title
HSA: A Heuristic Splice Alignment Tool
Published in
BMC Systems Biology, December 2013
DOI 10.1186/1752-0509-7-s2-s10
Pubmed ID
Authors

Jingde Bu, Xuebin Chi, Zhong Jin

Abstract

RNA-Seq methodology is a revolutionary transcriptomics sequencing technology, which is the representative of Next generation Sequencing (NGS). With the high throughput sequencing of RNA-Seq, we can acquire much more information like differential expression and novel splice variants from deep sequence analysis and data mining. But the short read length brings a great challenge to alignment, especially when the reads span two or more exons.

Twitter Demographics

The data shown below were collected from the profiles of 8 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 33%
Researcher 3 20%
Professor > Associate Professor 2 13%
Professor 1 7%
Student > Ph. D. Student 1 7%
Other 3 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 40%
Biochemistry, Genetics and Molecular Biology 4 27%
Unspecified 2 13%
Immunology and Microbiology 2 13%
Medicine and Dentistry 1 7%
Other 0 0%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 10 August 2017.
All research outputs
#2,013,769
of 12,378,406 outputs
Outputs from BMC Systems Biology
#105
of 1,040 outputs
Outputs of similar age
#31,978
of 194,860 outputs
Outputs of similar age from BMC Systems Biology
#4
of 38 outputs
Altmetric has tracked 12,378,406 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,040 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 89% 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 194,860 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 38 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.