Evidence map›Paper›PMID 27842607›Full record

ArticleJournal of biomedical semantics2016

The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants.

Robert Hoehndorf, Mona Alshahrani, Georgios V Gkoutos, George Gosline, Quentin Groom, Thomas Hamann, Jens Kattge, Sylvia Mota de Oliveira, Marco Schmidt, Soraya Sierra and 3 more

Abstract read
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Article in Journal of biomedical semantics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

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3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Enhancing the SIB Literature Services (SIBiLS) with annotations to support biocuration.Database : the journal of biological databases and curation · 2026
    Article
  3. Article
  4. The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.Mammalian genome : official journal of the International Mammalian Genome Society · 2023
    Article
  5. Review
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

13 authors.

Robert HoehndorfComputational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia. robert.hoehndorf@kaust.edu.sa.ORCID 0000-0001-8149-5890
Mona AlshahraniComputational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia.
Georgios V GkoutosCollege of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, B15 2TT, United Kingdom.
George GoslineRoyal Botanical Gardens, Kew, Richmond, Surrey, TW9 3AB, United Kingdom.
Quentin GroomBotanic Garden Meise, Nieuwelaan 38, Meise, 1860, Belgium.
Thomas HamannNaturalis Biodiversity Center, P.O. Box 9517, Leiden, 2300 RA, The Netherlands.
Jens KattgeMax Planck Institute for Biogeochemistry, Hans Knoell Str. 10, Jena, 07745, Germany.
Sylvia Mota de OliveiraNaturalis Biodiversity Center, P.O. Box 9517, Leiden, 2300 RA, The Netherlands.
Marco SchmidtSenckenberg Biodiversity and Climate Research Centre (BiK-F), Senckenberganlage 25, Frankfurt am Main, 60325, Germany.
Soraya SierraNaturalis Biodiversity Center, P.O. Box 9517, Leiden, 2300 RA, The Netherlands.
Erik SmetsNaturalis Biodiversity Center, P.O. Box 9517, Leiden, 2300 RA, The Netherlands.
Rutger A VosNaturalis Biodiversity Center, P.O. Box 9517, Leiden, 2300 RA, The Netherlands.
Claus WeilandSenckenberg Biodiversity and Climate Research Centre (BiK-F), Senckenberganlage 25, Frankfurt am Main, 60325, Germany.

Funding

Biotechnology and Biological Sciences Research Council BB/J004464/1
6 · The paper itself

Abstract

backgroundThe systematic analysis of a large number of comparable plant trait data can support investigations into phylogenetics and ecological adaptation, with broad applications in evolutionary biology, agriculture, conservation, and the functioning of ecosystems. Floras, i.e., books collecting the information on all known plant species found within a region, are a potentially rich source of such plant trait data. Floras describe plant traits with a focus on morphology and other traits relevant for species identification in addition to other characteristics of plant species, such as ecological affinities, distribution, economic value, health applications, traditional uses, and so on. However, a key limitation in systematically analyzing information in Floras is the lack of a standardized vocabulary for the described traits as well as the difficulties in extracting structured information from free text.

resultsWe have developed the Flora Phenotype Ontology (FLOPO), an ontology for describing traits of plant species found in Floras. We used the Plant Ontology (PO) and the Phenotype And Trait Ontology (PATO) to extract entity-quality relationships from digitized taxon descriptions in Floras, and used a formal ontological approach based on phenotype description patterns and automated reasoning to generate the FLOPO. The resulting ontology consists of 25,407 classes and is based on the PO and PATO. The classified ontology closely follows the structure of Plant Ontology in that the primary axis of classification is the observed plant anatomical structure, and more specific traits are then classified based on parthood and subclass relations between anatomical structures as well as subclass relations between phenotypic qualities.

conclusionsThe FLOPO is primarily intended as a framework based on which plant traits can be integrated computationally across all species and higher taxa of flowering plants. Importantly, it is not intended to replace established vocabularies or ontologies, but rather serve as an overarching framework based on which different application- and domain-specific ontologies, thesauri and vocabularies of phenotypes observed in flowering plants can be integrated.

Indexed as

Biological OntologiesPhenotypePlantsBiodiversityBotanyFloraMorphological traitsPhenotype

Identifiers

PMID27842607
PMCPMC5109718

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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.