CrossRef Text and Data Mining
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Choosing preferable labels for the Japanese translation of the Human Phenotype Ontology
Kota Ninomiya, Terue Takatsuki, Tatsuya Kushida, Yasunori Yamamoto, Soichi Ogishima
Genomics Inform. 2020;18(2):e23  Published online June 18, 2020
DOI: https://doi.org/10.5808/GI.2020.18.2.e23

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Choosing preferable labels for the Japanese translation of the Human Phenotype Ontology
Genomics & Informatics. 2020;18(2):e23   Crossref logo
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Machine enhanced translation of the Human Phenotype Ontology project
Procedia Computer Science. 2017;121:11-18   Crossref logo
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HPO2GO: prediction of human phenotype ontology term associations using cross ontology annotation co-occurrences
. 2018;   Crossref logo
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HPO2GO: prediction of human phenotype ontology term associations using cross ontology annotation co-occurrences
. 2018;   Crossref logo
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HPO2GO: prediction of human phenotype ontology term associations for proteins using cross ontology annotation co-occurrences
PeerJ. 2018;6:e5298   Crossref logo
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The Human Phenotype Ontology
Clinical Genetics. 2010;77(6):525-534   Crossref logo
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DiNGO: standalone application for Gene Ontology and Human Phenotype Ontology term enrichment analysis
Bioinformatics. 2019;   Crossref logo
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Biological and Medical Ontologies: Human Phenotype Ontology (HPO)
Encyclopedia of Bioinformatics and Computational Biology. 2019;848-857   Crossref logo
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PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources
F1000Research. 2015;4:259   Crossref logo
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Choosing a preferable strategy by the surrounding of a coalition in n-person games
Applied Mathematics Letters. 2003;16(5):689-694   Crossref logo
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