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Protein ontology on the semantic web for knowledge discovery
The Protein Ontology (PRO) provides an ontological representation of protein-related entities, ranging from protein families to proteoforms to complexes. Protein Ontology Linked Open Data (LOD) exposes, shares, and connects knowledge about protein-related entities on the Semantic Web using Resource...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7550340/ https://www.ncbi.nlm.nih.gov/pubmed/33046717 http://dx.doi.org/10.1038/s41597-020-00679-9 |
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author | Chen, Chuming Huang, Hongzhan Ross, Karen E. Cowart, Julie E. Arighi, Cecilia N. Wu, Cathy H. Natale, Darren A. |
author_facet | Chen, Chuming Huang, Hongzhan Ross, Karen E. Cowart, Julie E. Arighi, Cecilia N. Wu, Cathy H. Natale, Darren A. |
author_sort | Chen, Chuming |
collection | PubMed |
description | The Protein Ontology (PRO) provides an ontological representation of protein-related entities, ranging from protein families to proteoforms to complexes. Protein Ontology Linked Open Data (LOD) exposes, shares, and connects knowledge about protein-related entities on the Semantic Web using Resource Description Framework (RDF), thus enabling integration with other Linked Open Data for biological knowledge discovery. For example, proteins (or variants thereof) can be retrieved on the basis of specific disease associations. As a community resource, we strive to follow the Findability, Accessibility, Interoperability, and Reusability (FAIR) principles, disseminate regular updates of our data, support multiple methods for accessing, querying and downloading data in various formats, and provide documentation both for scientists and programmers. PRO Linked Open Data can be browsed via faceted browser interface and queried using SPARQL via YASGUI. RDF data dumps are also available for download. Additionally, we developed RESTful APIs to support programmatic data access. We also provide W3C HCLS specification compliant metadata description for our data. The PRO Linked Open Data is available at https://lod.proconsortium.org/. |
format | Online Article Text |
id | pubmed-7550340 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75503402020-10-19 Protein ontology on the semantic web for knowledge discovery Chen, Chuming Huang, Hongzhan Ross, Karen E. Cowart, Julie E. Arighi, Cecilia N. Wu, Cathy H. Natale, Darren A. Sci Data Article The Protein Ontology (PRO) provides an ontological representation of protein-related entities, ranging from protein families to proteoforms to complexes. Protein Ontology Linked Open Data (LOD) exposes, shares, and connects knowledge about protein-related entities on the Semantic Web using Resource Description Framework (RDF), thus enabling integration with other Linked Open Data for biological knowledge discovery. For example, proteins (or variants thereof) can be retrieved on the basis of specific disease associations. As a community resource, we strive to follow the Findability, Accessibility, Interoperability, and Reusability (FAIR) principles, disseminate regular updates of our data, support multiple methods for accessing, querying and downloading data in various formats, and provide documentation both for scientists and programmers. PRO Linked Open Data can be browsed via faceted browser interface and queried using SPARQL via YASGUI. RDF data dumps are also available for download. Additionally, we developed RESTful APIs to support programmatic data access. We also provide W3C HCLS specification compliant metadata description for our data. The PRO Linked Open Data is available at https://lod.proconsortium.org/. Nature Publishing Group UK 2020-10-12 /pmc/articles/PMC7550340/ /pubmed/33046717 http://dx.doi.org/10.1038/s41597-020-00679-9 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Chen, Chuming Huang, Hongzhan Ross, Karen E. Cowart, Julie E. Arighi, Cecilia N. Wu, Cathy H. Natale, Darren A. Protein ontology on the semantic web for knowledge discovery |
title | Protein ontology on the semantic web for knowledge discovery |
title_full | Protein ontology on the semantic web for knowledge discovery |
title_fullStr | Protein ontology on the semantic web for knowledge discovery |
title_full_unstemmed | Protein ontology on the semantic web for knowledge discovery |
title_short | Protein ontology on the semantic web for knowledge discovery |
title_sort | protein ontology on the semantic web for knowledge discovery |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7550340/ https://www.ncbi.nlm.nih.gov/pubmed/33046717 http://dx.doi.org/10.1038/s41597-020-00679-9 |
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