↓ Skip to main content

GOTA: GO term annotation of biomedical literature

Overview of attention for article published in BMC Bioinformatics, October 2015
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 X users

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
34 Mendeley
citeulike
2 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
GOTA: GO term annotation of biomedical literature
Published in
BMC Bioinformatics, October 2015
DOI 10.1186/s12859-015-0777-8
Pubmed ID
Authors

Pietro Di Lena, Giacomo Domeniconi, Luciano Margara, Gianluca Moro

Abstract

Functional annotation of genes and gene products is a major challenge in the post-genomic era. Nowadays, gene function curation is largely based on manual assignment of Gene Ontology (GO) annotations to genes by using published literature. The annotation task is extremely time-consuming, therefore there is an increasing interest in automated tools that can assist human experts. Here we introduce GOTA, a GO term annotator for biomedical literature. The proposed approach makes use only of information that is readily available from public repositories and it is easily expandable to handle novel sources of information. We assess the classification capabilities of GOTA on a large benchmark set of publications. The overall performances are encouraging in comparison to the state of the art in multi-label classification over large taxonomies. Furthermore, the experimental tests provide some interesting insights into the potential improvement of automated annotation tools. GOTA implements a flexible and expandable model for GO annotation of biomedical literature. The current version of the GOTA tool is freely available at http://gota.apice.unibo.it .

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Unknown 33 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 21%
Student > Bachelor 4 12%
Student > Master 4 12%
Professor 2 6%
Student > Ph. D. Student 2 6%
Other 4 12%
Unknown 11 32%
Readers by discipline Count As %
Computer Science 13 38%
Agricultural and Biological Sciences 4 12%
Engineering 3 9%
Biochemistry, Genetics and Molecular Biology 2 6%
Chemistry 1 3%
Other 1 3%
Unknown 10 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 11 November 2015.
All research outputs
#13,449,870
of 22,831,537 outputs
Outputs from BMC Bioinformatics
#4,199
of 7,288 outputs
Outputs of similar age
#135,143
of 284,642 outputs
Outputs of similar age from BMC Bioinformatics
#79
of 157 outputs
Altmetric has tracked 22,831,537 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,288 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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 284,642 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 50% of its contemporaries.
We're also able to compare this research output to 157 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.