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Textpresso Central: a customizable platform for searching, text mining, viewing, and curating biomedical literature

Overview of attention for article published in BMC Bioinformatics, March 2018
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

twitter
6 tweeters

Citations

dimensions_citation
32 Dimensions

Readers on

mendeley
86 Mendeley
citeulike
3 CiteULike
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Title
Textpresso Central: a customizable platform for searching, text mining, viewing, and curating biomedical literature
Published in
BMC Bioinformatics, March 2018
DOI 10.1186/s12859-018-2103-8
Pubmed ID
Authors

H.-M. Müller, K. M. Van Auken, Y. Li, P. W. Sternberg

Abstract

The biomedical literature continues to grow at a rapid pace, making the challenge of knowledge retrieval and extraction ever greater. Tools that provide a means to search and mine the full text of literature thus represent an important way by which the efficiency of these processes can be improved. We describe the next generation of the Textpresso information retrieval system, Textpresso Central (TPC). TPC builds on the strengths of the original system by expanding the full text corpus to include the PubMed Central Open Access Subset (PMC OA), as well as the WormBase C. elegans bibliography. In addition, TPC allows users to create a customized corpus by uploading and processing documents of their choosing. TPC is UIMA compliant, to facilitate compatibility with external processing modules, and takes advantage of Lucene indexing and search technology for efficient handling of millions of full text documents. Like Textpresso, TPC searches can be performed using keywords and/or categories (semantically related groups of terms), but to provide better context for interpreting and validating queries, search results may now be viewed as highlighted passages in the context of full text. To facilitate biocuration efforts, TPC also allows users to select text spans from the full text and annotate them, create customized curation forms for any data type, and send resulting annotations to external curation databases. As an example of such a curation form, we describe integration of TPC with the Noctua curation tool developed by the Gene Ontology (GO) Consortium. Textpresso Central is an online literature search and curation platform that enables biocurators and biomedical researchers to search and mine the full text of literature by integrating keyword and category searches with viewing search results in the context of the full text. It also allows users to create customized curation interfaces, use those interfaces to make annotations linked to supporting evidence statements, and then send those annotations to any database in the world. Textpresso Central URL: http://www.textpresso.org/tpc.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 86 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 27%
Student > Master 13 15%
Student > Ph. D. Student 12 14%
Student > Bachelor 11 13%
Other 3 3%
Other 7 8%
Unknown 17 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 29%
Computer Science 13 15%
Biochemistry, Genetics and Molecular Biology 10 12%
Medicine and Dentistry 5 6%
Social Sciences 3 3%
Other 10 12%
Unknown 20 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 19 March 2018.
All research outputs
#3,753,020
of 13,791,430 outputs
Outputs from BMC Bioinformatics
#1,677
of 5,139 outputs
Outputs of similar age
#93,178
of 274,232 outputs
Outputs of similar age from BMC Bioinformatics
#4
of 25 outputs
Altmetric has tracked 13,791,430 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 5,139 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 67% 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 274,232 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 65% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.