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OsteoporosAtlas: a human osteoporosis-related gene database
BACKGROUND: Osteoporosis is a common, complex disease of bone with a strong heritable component, characterized by low bone mineral density, microarchitectural deterioration of bone tissue and an increased risk of fracture. Due to limited drug selection for osteoporosis and increasing morbidity, mort...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6487800/ https://www.ncbi.nlm.nih.gov/pubmed/31086734 http://dx.doi.org/10.7717/peerj.6778 |
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author | Wang, Xun Diao, Lihong Sun, Dezhi Wang, Dan Zhu, Jiarun He, Yangzhige Liu, Yuan Xu, Hao Zhang, Yi Liu, Jinying Wang, Yan He, Fuchu Li, Yang Li, Dong |
author_facet | Wang, Xun Diao, Lihong Sun, Dezhi Wang, Dan Zhu, Jiarun He, Yangzhige Liu, Yuan Xu, Hao Zhang, Yi Liu, Jinying Wang, Yan He, Fuchu Li, Yang Li, Dong |
author_sort | Wang, Xun |
collection | PubMed |
description | BACKGROUND: Osteoporosis is a common, complex disease of bone with a strong heritable component, characterized by low bone mineral density, microarchitectural deterioration of bone tissue and an increased risk of fracture. Due to limited drug selection for osteoporosis and increasing morbidity, mortality of osteoporotic fractures, osteoporosis has become a major health burden in aging societies. Current researches for identifying specific loci or genes involved in osteoporosis contribute to a greater understanding of the pathogenesis of osteoporosis and the development of better diagnosis, prevention and treatment strategies. However, little is known about how most causal genes work and interact to influence osteoporosis. Therefore, it is greatly significant to collect and analyze the studies involved in osteoporosis-related genes. Unfortunately, the information about all these osteoporosis-related genes is scattered in a large amount of extensive literature. Currently, there is no specialized database for easily accessing relevant information about osteoporosis-related genes and miRNAs. METHODS: We extracted data from literature abstracts in PubMed by text-mining and manual curation. Moreover, a local MySQL database containing all the data was developed with PHP on a Windows server. RESULTS: OsteoporosAtlas (http://biokb.ncpsb.org/osteoporosis/), the first specialized database for easily accessing relevant information such as osteoporosis-related genes and miRNAs, was constructed and served for researchers. OsteoporosAtlas enables users to retrieve, browse and download osteoporosis-related genes and miRNAs. Gene ontology and pathway analyses were integrated into OsteoporosAtlas. It currently includes 617 human encoding genes, 131 human non-coding miRNAs, and 128 functional roles. We think that OsteoporosAtlas will be an important bioinformatics resource to facilitate a better understanding of the pathogenesis of osteoporosis and developing better diagnosis, prevention and treatment strategies. |
format | Online Article Text |
id | pubmed-6487800 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-64878002019-05-13 OsteoporosAtlas: a human osteoporosis-related gene database Wang, Xun Diao, Lihong Sun, Dezhi Wang, Dan Zhu, Jiarun He, Yangzhige Liu, Yuan Xu, Hao Zhang, Yi Liu, Jinying Wang, Yan He, Fuchu Li, Yang Li, Dong PeerJ Bioinformatics BACKGROUND: Osteoporosis is a common, complex disease of bone with a strong heritable component, characterized by low bone mineral density, microarchitectural deterioration of bone tissue and an increased risk of fracture. Due to limited drug selection for osteoporosis and increasing morbidity, mortality of osteoporotic fractures, osteoporosis has become a major health burden in aging societies. Current researches for identifying specific loci or genes involved in osteoporosis contribute to a greater understanding of the pathogenesis of osteoporosis and the development of better diagnosis, prevention and treatment strategies. However, little is known about how most causal genes work and interact to influence osteoporosis. Therefore, it is greatly significant to collect and analyze the studies involved in osteoporosis-related genes. Unfortunately, the information about all these osteoporosis-related genes is scattered in a large amount of extensive literature. Currently, there is no specialized database for easily accessing relevant information about osteoporosis-related genes and miRNAs. METHODS: We extracted data from literature abstracts in PubMed by text-mining and manual curation. Moreover, a local MySQL database containing all the data was developed with PHP on a Windows server. RESULTS: OsteoporosAtlas (http://biokb.ncpsb.org/osteoporosis/), the first specialized database for easily accessing relevant information such as osteoporosis-related genes and miRNAs, was constructed and served for researchers. OsteoporosAtlas enables users to retrieve, browse and download osteoporosis-related genes and miRNAs. Gene ontology and pathway analyses were integrated into OsteoporosAtlas. It currently includes 617 human encoding genes, 131 human non-coding miRNAs, and 128 functional roles. We think that OsteoporosAtlas will be an important bioinformatics resource to facilitate a better understanding of the pathogenesis of osteoporosis and developing better diagnosis, prevention and treatment strategies. PeerJ Inc. 2019-04-26 /pmc/articles/PMC6487800/ /pubmed/31086734 http://dx.doi.org/10.7717/peerj.6778 Text en ©2019 Wang et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Wang, Xun Diao, Lihong Sun, Dezhi Wang, Dan Zhu, Jiarun He, Yangzhige Liu, Yuan Xu, Hao Zhang, Yi Liu, Jinying Wang, Yan He, Fuchu Li, Yang Li, Dong OsteoporosAtlas: a human osteoporosis-related gene database |
title | OsteoporosAtlas: a human osteoporosis-related gene database |
title_full | OsteoporosAtlas: a human osteoporosis-related gene database |
title_fullStr | OsteoporosAtlas: a human osteoporosis-related gene database |
title_full_unstemmed | OsteoporosAtlas: a human osteoporosis-related gene database |
title_short | OsteoporosAtlas: a human osteoporosis-related gene database |
title_sort | osteoporosatlas: a human osteoporosis-related gene database |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6487800/ https://www.ncbi.nlm.nih.gov/pubmed/31086734 http://dx.doi.org/10.7717/peerj.6778 |
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