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Introducing meta-services for biomedical information extraction

Overview of attention for article published in Genome Biology, September 2008
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1 X user

Citations

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59 Dimensions

Readers on

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88 Mendeley
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13 CiteULike
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4 Connotea
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Title
Introducing meta-services for biomedical information extraction
Published in
Genome Biology, September 2008
DOI 10.1186/gb-2008-9-s2-s6
Pubmed ID
Authors

Florian Leitner, Martin Krallinger, Carlos Rodriguez-Penagos, Jörg Hakenberg, Conrad Plake, Cheng-Ju Kuo, Chun-Nan Hsu, Richard Tzong-Han Tsai, Hsi-Chuan Hung, William W Lau, Calvin A Johnson, Rune Sætre, Kazuhiro Yoshida, Yan Hua Chen, Sun Kim, Soo-Yong Shin, Byoung-Tak Zhang, William A Baumgartner, Lawrence Hunter, Barry Haddow, Michael Matthews, Xinglong Wang, Patrick Ruch, Frédéric Ehrler, Arzucan Özgür, Güneş Erkan, Dragomir R Radev, Michael Krauthammer, ThaiBinh Luong, Robert Hoffmann, Chris Sander, Alfonso Valencia

Abstract

We introduce the first meta-service for information extraction in molecular biology, the BioCreative MetaServer (BCMS; http://bcms.bioinfo.cnio.es/). This prototype platform is a joint effort of 13 research groups and provides automatically generated annotations for PubMed/Medline abstracts. Annotation types cover gene names, gene IDs, species, and protein-protein interactions. The annotations are distributed by the meta-server in both human and machine readable formats (HTML/XML). This service is intended to be used by biomedical researchers and database annotators, and in biomedical language processing. The platform allows direct comparison, unified access, and result aggregation of the annotations.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 10%
Spain 5 6%
United Kingdom 2 2%
Netherlands 1 1%
France 1 1%
Sweden 1 1%
Canada 1 1%
Germany 1 1%
Denmark 1 1%
Other 3 3%
Unknown 63 72%

Demographic breakdown

Readers by professional status Count As %
Researcher 31 35%
Student > Ph. D. Student 16 18%
Professor 7 8%
Other 7 8%
Professor > Associate Professor 7 8%
Other 15 17%
Unknown 5 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 40%
Computer Science 27 31%
Biochemistry, Genetics and Molecular Biology 3 3%
Linguistics 3 3%
Medicine and Dentistry 3 3%
Other 6 7%
Unknown 11 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 07 October 2013.
All research outputs
#20,655,488
of 25,371,288 outputs
Outputs from Genome Biology
#4,269
of 4,467 outputs
Outputs of similar age
#88,563
of 95,711 outputs
Outputs of similar age from Genome Biology
#31
of 32 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.