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      The vertebrate taxonomy ontology: a framework for reasoning across model organism and species phenotypes

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          Abstract

          Background

          A hierarchical taxonomy of organisms is a prerequisite for semantic integration of biodiversity data. Ideally, there would be a single, expansive, authoritative taxonomy that includes extinct and extant taxa, information on synonyms and common names, and monophyletic supraspecific taxa that reflect our current understanding of phylogenetic relationships.

          Description

          As a step towards development of such a resource, and to enable large-scale integration of phenotypic data across vertebrates, we created the Vertebrate Taxonomy Ontology (VTO), a semantically defined taxonomic resource derived from the integration of existing taxonomic compilations, and freely distributed under a Creative Commons Zero (CC0) public domain waiver. The VTO includes both extant and extinct vertebrates and currently contains 106,947 taxonomic terms, 22 taxonomic ranks, 104,736 synonyms, and 162,400 cross-references to other taxonomic resources. Key challenges in constructing the VTO included (1) extracting and merging names, synonyms, and identifiers from heterogeneous sources; (2) structuring hierarchies of terms based on evolutionary relationships and the principle of monophyly; and (3) automating this process as much as possible to accommodate updates in source taxonomies.

          Conclusions

          The VTO is the primary source of taxonomic information used by the Phenoscape Knowledgebase ( http://phenoscape.org/), which integrates genetic and evolutionary phenotype data across both model and non-model vertebrates. The VTO is useful for inferring phenotypic changes on the vertebrate tree of life, which enables queries for candidate genes for various episodes in vertebrate evolution.

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          Most cited references4

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          A Radical Solution to the Species Problem

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            500,000 fish phenotypes: The new informatics landscape for evolutionary and developmental biology of the vertebrate skeleton

            The rich phenotypic diversity that characterizes the vertebrate skeleton results from evolutionary changes in regulation of genes that drive development. Although relatively little is known about the genes that underlie the skeletal variation among fish species, significant knowledge of genetics and development is available for zebrafish. Because developmental processes are highly conserved, this knowledge can be leveraged for understanding the evolution of skeletal diversity. We developed the Phenoscape Knowledgebase (KB; http://kb.phenoscape.org) to yield testable hypotheses of candidate genes involved in skeletal evolution. We developed a community anatomy ontology for fishes and ontology-based methods to represent complex free-text character descriptions of species in a computable format. With these tools, we populated the KB with comparative morphological data from the literature on over 2500 teleost fishes (mainly Ostariophysi) resulting in over 500,000 taxon phenotype annotations. The KB integrates these data with similarly structured phenotype data from zebrafish genes (http://zfin.org). Using ontology-based reasoning, candidate genes can be inferred for the phenotypes that vary across taxa, thereby uniting genetic and phenotypic data to formulate evo-devo hypotheses. The morphological data in the KB can be browsed, sorted, and aggregated in ways that provide unprecedented possibilities for data mining and discovery.
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              Phylogenetic Analysis of the Asian Cyprinid Genus Danio (Teleostei, Cyprinidae)

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                Author and article information

                Contributors
                Journal
                J Biomed Semantics
                J Biomed Semantics
                Journal of Biomedical Semantics
                BioMed Central
                2041-1480
                2013
                22 November 2013
                : 4
                : 34
                Affiliations
                [1 ]Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, Kansas, USA
                [2 ]National Evolutionary Synthesis Center, Durham, North Carolina, USA
                [3 ]Department of Biology, University of South Dakota, Vermillion, South Dakota, USA
                [4 ]Department of Biology, University of North Carolina, Chapel Hill, North Carolina, USA
                [5 ]Department of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois, USA
                [6 ]Academy of Natural Sciences, Philadelphia, Pennsylvania, USA
                [7 ]Institute of Neuroscience, University of Oregon, Eugene, Oregon, USA
                [8 ]Department of Vertebrate Zoology and Anthropology, California Academy of Sciences, San Francisco, California, USA
                Article
                2041-1480-4-34
                10.1186/2041-1480-4-34
                4177199
                24267744
                e2e8466b-d330-4d2f-ae2d-1d38a7f0e713
                Copyright © 2013 Midford et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 1 June 2013
                : 7 October 2013
                Categories
                Database

                Bioinformatics & Computational biology
                data integration,evolutionary biology,paleontology,taxonomic rank

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