Evidence map›Paper›PMID 26072502›Full record

ArticleBioinformatics (Oxford, England)2015

Knowledge-driven geospatial location resolution for phylogeographic models of virus migration.

Davy Weissenbacher, Tasnia Tahsin, Rachel Beard, Mari Figaro, Robert Rivera, Matthew Scotch, Graciela Gonzalez

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Bi-directional Recurrent Neural Network Models for Geographic Location Extraction in Biomedical Literature.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2019
    Article
  6. Article
  7. Article
  8. Extracting geographic locations from the literature for virus phylogeography using supervised and distant supervision methods.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2017
    Article
  9. Collaborative relation annotation and quality analysis in Markyt environment.Database : the journal of biological databases and curation · 2017
    Article
  10. Named entity linking of geospatial and host metadata in GenBank for advancing biomedical research.Database : the journal of biological databases and curation · 2017
    Article
  11. A high-precision rule-based extraction system for expanding geospatial metadata in GenBank records.Journal of the American Medical Informatics Association : JAMIA · 2016
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Davy WeissenbacherDepartment of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA and Center for Environmental Security, Biodesign Institute, Arizona State University, Tempe, AZ 85287-5904, USA.
Tasnia TahsinDepartment of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA and Center for Environmental Security, Biodesign Institute, Arizona State University, Tempe, AZ 85287-5904, USA.
Rachel BeardDepartment of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA and Center for Environmental Security, Biodesign Institute, Arizona State University, Tempe, AZ 85287-5904, USA Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA and Center for Environmental Security, Biodesign Institute, Arizona State University, Tempe, AZ 85287-5904, USA.
Mari FigaroDepartment of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA and Center for Environmental Security, Biodesign Institute, Arizona State University, Tempe, AZ 85287-5904, USA Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA and Center for Environmental Security, Biodesign Institute, Arizona State University, Tempe, AZ 85287-5904, USA.
Robert RiveraDepartment of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA and Center for Environmental Security, Biodesign Institute, Arizona State University, Tempe, AZ 85287-5904, USA.
Matthew ScotchDepartment of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA and Center for Environmental Security, Biodesign Institute, Arizona State University, Tempe, AZ 85287-5904, USA Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA and Center for Environmental Security, Biodesign Institute, Arizona State University, Tempe, AZ 85287-5904, USA.
Graciela GonzalezDepartment of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA and Center for Environmental Security, Biodesign Institute, Arizona State University, Tempe, AZ 85287-5904, USA.

Funding

Text Processing and Geospatial Uncertainty for Phylogeography of Zoonotic VirusesR56AI102559 · NIAID · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI GONZALEZ HERNANDEZ, GRACIELA, SCOTCH, MATTHEW · 2013 to 2013
$451k
NIAID NIH HHS R56AI102559
6 · The paper itself

Abstract

unlabelledDiseases caused by zoonotic viruses (viruses transmittable between humans and animals) are a major threat to public health throughout the world. By studying virus migration and mutation patterns, the field of phylogeography provides a valuable tool for improving their surveillance. A key component in phylogeographic analysis of zoonotic viruses involves identifying the specific locations of relevant viral sequences. This is usually accomplished by querying public databases such as GenBank and examining the geospatial metadata in the record. When sufficient detail is not available, a logical next step is for the researcher to conduct a manual survey of the corresponding published articles. MOTIVATION: In this article, we present a system for detection and disambiguation of locations (toponym resolution) in full-text articles to automate the retrieval of sufficient metadata. Our system has been tested on a manually annotated corpus of journal articles related to phylogeography using integrated heuristics for location disambiguation including a distance heuristic, a population heuristic and a novel heuristic utilizing knowledge obtained from GenBank metadata (i.e. a 'metadata heuristic').

resultsFor detecting and disambiguating locations, our system performed best using the metadata heuristic (0.54 Precision, 0.89 Recall and 0.68 F-score). Precision reaches 0.88 when examining only the disambiguation of location names. Our error analysis showed that a noticeable increase in the accuracy of toponym resolution is possible by improving the geospatial location detection. By improving these fundamental automated tasks, our system can be a useful resource to phylogeographers that rely on geospatial metadata of GenBank sequences. .

Indexed as

Databases, Nucleic AcidPhylogeographySequence AnalysisViruses

Identifiers

PMID26072502
PMCPMC4542781

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.