ArticleJournal of biomedical semantics2015
Expanding the mammalian phenotype ontology to support automated exchange of high throughput mouse phenotyping data generated by large-scale mouse knockout screens.
Article in Journal of biomedical semantics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- Expanding and refining the Mammalian Phenotype Ontology to enhance disease model discovery.Disease models & mechanisms · 2025Article
- Multi-tool copy number detection highlights common body size-associated variants in miniature pig breeds from different geographical regions.BMC genomics · 2025Article
- Improving prenatal diagnosis through standards and aggregation.Prenatal diagnosis · 2024Review
- Rare disease research resources at the Rat Genome Database.Genetics · 2023Article
- IAnimal: a cross-species omics knowledgebase for animals.Nucleic acids research · 2023Article
- Altered hair root gene expression profiles highlight calcium signaling and lipid metabolism pathways to be associated with curly hair initiation and maintenance in Mangalitza pigs.Frontiers in genetics · 2023Article
- WhichTF is functionally important in your open chromatin data?PLoS computational biology · 2022Article
- The Xenopus phenotype ontology: bridging model organism phenotype data to human health and development.BMC bioinformatics · 2022Article
- Pleiotropy data resource as a primer for investigating co-morbidities/multi-morbidities and their role in disease.Mammalian genome : official journal of the International Mammalian Genome Society · 2022Article
- The Human Disease Ontology 2022 update.Nucleic acids research · 2022Article
- Mouse Genome Database (MGD): Knowledgebase for mouse-human comparative biology.Nucleic acids research · 2021Article
- Dimensional reduction of phenotypes from 53 000 mouse models reveals a diverse landscape of gene function.Bioinformatics advances · 2021Article
- DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier.PLoS computational biology · 2020Article
- DDIEM: drug database for inborn errors of metabolism.Orphanet journal of rare diseases · 2020Article
- Formal axioms in biomedical ontologies improve analysis and interpretation of associated data.Bioinformatics (Oxford, England) · 2020Article
- Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology.Nature communications · 2019Article
- New models for human disease from the International Mouse Phenotyping Consortium.Mammalian genome : official journal of the International Mammalian Genome Society · 2019Review
- Xenbase: Facilitating the Use ofFrontiers in physiology · 2019Review
- The anatomy of phenotype ontologies: principles, properties and applications.Briefings in bioinformatics · 2018Article
- Ontology-based validation and identification of regulatory phenotypes.Bioinformatics (Oxford, England) · 2018Article
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2 authors.
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Abstract
backgroundA vast array of data is about to emerge from the large scale high-throughput mouse knockout phenotyping projects worldwide. It is critical that this information is captured in a standardized manner, made accessible, and is fully integrated with other phenotype data sets for comprehensive querying and analysis across all phenotype data types. The volume of data generated by the high-throughput phenotyping screens is expected to grow exponentially, thus, automated methods and standards to exchange phenotype data are required.
resultsThe IMPC (International Mouse Phenotyping Consortium) is using the Mammalian Phenotype (MP) ontology in the automated annotation of phenodeviant data from high throughput phenotyping screens. 287 new term additions with additional hierarchy revisions were made in multiple branches of the MP ontology to accurately describe the results generated by these high throughput screens.
conclusionsBecause these large scale phenotyping data sets will be reported using the MP as the common data standard for annotation and data exchange, automated importation of these data to MGI (Mouse Genome Informatics) and other resources is possible without curatorial effort. Maximum biomedical value of these mutant mice will come from integrating primary high-throughput phenotyping data with secondary, comprehensive phenotypic analyses combined with published phenotype details on these and related mutants at MGI and other resources.
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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.