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Investigations on factors influencing HPO-based semantic similarity calculation
BACKGROUND: Although disease diagnosis has greatly benefited from next generation sequencing technologies, it is still difficult to make the right diagnosis purely based on sequencing technologies for many diseases with complex phenotypes and high genetic heterogeneity. Recently, calculating Human P...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5763495/ https://www.ncbi.nlm.nih.gov/pubmed/29297376 http://dx.doi.org/10.1186/s13326-017-0144-y |
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author | Peng, Jiajie Li, Qianqian Shang, Xuequn |
author_facet | Peng, Jiajie Li, Qianqian Shang, Xuequn |
author_sort | Peng, Jiajie |
collection | PubMed |
description | BACKGROUND: Although disease diagnosis has greatly benefited from next generation sequencing technologies, it is still difficult to make the right diagnosis purely based on sequencing technologies for many diseases with complex phenotypes and high genetic heterogeneity. Recently, calculating Human Phenotype Ontology (HPO)-based phenotype semantic similarity has contributed a lot for completing disease diagnosis. However, factors which affect the accuracy of HPO-based semantic similarity have not been evaluated systematically. RESULTS: In this study, we proposed a new framework called HPOFactor to evaluate these factors. Our model includes four components: (1) the size of annotation set, (2) the evidence code of annotations, (3) the quality of annotations and (4) the coverage of annotations respectively. CONCLUSIONS: HPOFactor analyzes the four factors systematically based on two kinds of experiments: causative gene prediction and disease prediction. Furthermore, semantic similarity measurement could be designed based on the characteristic of these factors. |
format | Online Article Text |
id | pubmed-5763495 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57634952018-01-17 Investigations on factors influencing HPO-based semantic similarity calculation Peng, Jiajie Li, Qianqian Shang, Xuequn J Biomed Semantics Research BACKGROUND: Although disease diagnosis has greatly benefited from next generation sequencing technologies, it is still difficult to make the right diagnosis purely based on sequencing technologies for many diseases with complex phenotypes and high genetic heterogeneity. Recently, calculating Human Phenotype Ontology (HPO)-based phenotype semantic similarity has contributed a lot for completing disease diagnosis. However, factors which affect the accuracy of HPO-based semantic similarity have not been evaluated systematically. RESULTS: In this study, we proposed a new framework called HPOFactor to evaluate these factors. Our model includes four components: (1) the size of annotation set, (2) the evidence code of annotations, (3) the quality of annotations and (4) the coverage of annotations respectively. CONCLUSIONS: HPOFactor analyzes the four factors systematically based on two kinds of experiments: causative gene prediction and disease prediction. Furthermore, semantic similarity measurement could be designed based on the characteristic of these factors. BioMed Central 2017-09-20 /pmc/articles/PMC5763495/ /pubmed/29297376 http://dx.doi.org/10.1186/s13326-017-0144-y Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Peng, Jiajie Li, Qianqian Shang, Xuequn Investigations on factors influencing HPO-based semantic similarity calculation |
title | Investigations on factors influencing HPO-based semantic similarity calculation |
title_full | Investigations on factors influencing HPO-based semantic similarity calculation |
title_fullStr | Investigations on factors influencing HPO-based semantic similarity calculation |
title_full_unstemmed | Investigations on factors influencing HPO-based semantic similarity calculation |
title_short | Investigations on factors influencing HPO-based semantic similarity calculation |
title_sort | investigations on factors influencing hpo-based semantic similarity calculation |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5763495/ https://www.ncbi.nlm.nih.gov/pubmed/29297376 http://dx.doi.org/10.1186/s13326-017-0144-y |
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