↓ Skip to main content

A text-mining system for extracting metabolic reactions from full-text articles

Overview of attention for article published in BMC Bioinformatics, July 2012
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (74th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
8 X users

Citations

dimensions_citation
31 Dimensions

Readers on

mendeley
106 Mendeley
citeulike
11 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A text-mining system for extracting metabolic reactions from full-text articles
Published in
BMC Bioinformatics, July 2012
DOI 10.1186/1471-2105-13-172
Pubmed ID
Authors

Jan Czarnecki, Irene Nobeli, Adrian M Smith, Adrian J Shepherd

Abstract

Increasingly biological text mining research is focusing on the extraction of complex relationships relevant to the construction and curation of biological networks and pathways. However, one important category of pathway - metabolic pathways - has been largely neglected.Here we present a relatively simple method for extracting metabolic reaction information from free text that scores different permutations of assigned entities (enzymes and metabolites) within a given sentence based on the presence and location of stemmed keywords. This method extends an approach that has proved effective in the context of the extraction of protein-protein interactions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 4 4%
Netherlands 2 2%
Germany 2 2%
United States 2 2%
United Kingdom 2 2%
Switzerland 1 <1%
France 1 <1%
Canada 1 <1%
Portugal 1 <1%
Other 4 4%
Unknown 86 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 32 30%
Student > Ph. D. Student 20 19%
Student > Master 16 15%
Student > Doctoral Student 6 6%
Student > Bachelor 4 4%
Other 18 17%
Unknown 10 9%
Readers by discipline Count As %
Computer Science 34 32%
Agricultural and Biological Sciences 32 30%
Biochemistry, Genetics and Molecular Biology 11 10%
Chemistry 4 4%
Linguistics 2 2%
Other 10 9%
Unknown 13 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 July 2013.
All research outputs
#6,418,689
of 25,079,131 outputs
Outputs from BMC Bioinformatics
#2,246
of 7,644 outputs
Outputs of similar age
#42,581
of 169,930 outputs
Outputs of similar age from BMC Bioinformatics
#18
of 89 outputs
Altmetric has tracked 25,079,131 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 7,644 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 70% 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 169,930 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 74% of its contemporaries.
We're also able to compare this research output to 89 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.