ArticleApplications in plant sciences2018
Extraction of phenotypic traits from taxonomic descriptions for the tree of life using natural language processing.
Article in Applications in plant sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Making floras computable: Audited translation of flora of China as reusable taxonomic knowledge.Plant diversity · 2026Article
- Rhizosphere Microbiome Engineering for Climate-Smart Agriculture: From Synthetic Consortia to Precision Decision Support.Microorganisms · 2026Review
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- Inferring microbiota functions from taxonomic genes: a review.GigaScience · 2022Review
- Diatoms.org: supporting taxonomists, connecting communities.Diatom research : the journal of the International Society for Diatom Research · 2022Article
- Extracting knowledge networks from plant scientific literature: potato tuber flesh color as an exemplary trait.BMC plant biology · 2021Article
- Article
- Extraction of phenotypic traits from taxonomic descriptions for the tree of life using natural language processing.Applications in plant sciences · 2018Article
- Resolving "orphaned" non-specific structures using machine learning and natural language processing methods.Biodiversity data journal · 2018Article
- Using large language models to extract plant functional traits from unstructured text.Applications in plant sciencesArticle
- Fully automatic extraction of morphological traits from the web: Utopia or reality?Applications in plant sciencesArticle
- FloraTraiter: Automated parsing of traits from descriptive biodiversity literature.Applications in plant sciencesArticle
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
premise of the studyPhenotypic data sets are necessary to elucidate the genealogy of life, but assembling phenotypic data for taxa across the tree of life can be technically challenging and prohibitively time consuming. We describe a semi-automated protocol to facilitate and expedite the assembly of phenotypic character matrices of plants from formal taxonomic descriptions. This pipeline uses new natural language processing (NLP) techniques and a glossary of over 9000 botanical terms. METHODS AND
resultsOur protocol includes the Explorer of Taxon Concepts (ETC), an online application that assembles taxon-by-character matrices from taxonomic descriptions, and MatrixConverter, a Java application that enables users to evaluate and discretize the characters extracted by ETC. We demonstrate this protocol using descriptions from Araucariaceae.
conclusionsThe NLP pipeline unlocks the phenotypic data found in taxonomic descriptions and makes them usable for evolutionary analyses.
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