The SPECIES and ORGANISMS Resources for Fast and Accurate Identification of Taxonomic Names in Text

The SPECIES and ORGANISMS Resources for Fast and Accurate Identification of Taxonomic Names in Text

The exponential growth of the biomedical literature is making the need for efficient, accurate text-mining tools increasingly clear. The identification of named biological entities in text is a central and difficult task. We have developed an efficient algorithm and implementation of a dictionary-ba...

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Bibliographic Details
Published in:PloS one 2013-06, Vol.8 (6), p.e65390-e65390
Main Authors: Pafilis, Evangelos, Frankild, Sune P, Fanini, Lucia, Faulwetter, Sarah, Pavloudi, Christina, Vasileiadou, Aikaterini, Arvanitidis, Christos, Jensen, Lars Juhl
Format: Article
Language:eng
Subjects:
Agreements
Aquaculture
Biodiversity
Bioinformatics
Biological effects
Biology
Biotechnology
Classification
Computer Science
Data Mining - methods
Dictionaries
Engineering
Gold
Health sciences
Identification
Informatics
Internet
Marine biology
Mining
Names
Open source software
Organisms
Proteins
Researchers
Species
Taxa
Taxonomy
Terminology as Topic
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Summary:The exponential growth of the biomedical literature is making the need for efficient, accurate text-mining tools increasingly clear. The identification of named biological entities in text is a central and difficult task. We have developed an efficient algorithm and implementation of a dictionary-based approach to named entity recognition, which we here use to identify names of species and other taxa in text. The tool, SPECIES, is more than an order of magnitude faster and as accurate as existing tools. The precision and recall was assessed both on an existing gold-standard corpus and on a new corpus of 800 abstracts, which were manually annotated after the development of the tool. The corpus comprises abstracts from journals selected to represent many taxonomic groups, which gives insights into which types of organism names are hard to detect and which are easy. Finally, we have tagged organism names in the entire Medline database and developed a web resource, ORGANISMS, that makes the results accessible to the broad community of biologists. The SPECIES software is open source and can be downloaded from http://species.jensenlab.org along with dictionary files and the manually annotated gold-standard corpus. The ORGANISMS web resource can be found at http://organisms.jensenlab.org.
ISSN:1932-6203
1932-6203