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ATD: a comprehensive bioinformatics resource for deciphering the association of autophagy and diseases
Autophagy is the natural, regulated, destructive mechanism of the eukaryotes cell that disassembles unnecessary or dysfunctional components. In recent years, the association between autophagy and diseases has attracted more and more attention, but our understanding of the molecular mechanism about t...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6146119/ https://www.ncbi.nlm.nih.gov/pubmed/30239683 http://dx.doi.org/10.1093/database/bay093 |
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author | Wang, Wenjing Zhang, Peng Li, Leijie Chen, Zhaobin Bai, Weiyang Liu, Guiyou Zhang, Liangcai Jia, Haiyang Li, Li Yu, Yingcui Liao, Mingzhi |
author_facet | Wang, Wenjing Zhang, Peng Li, Leijie Chen, Zhaobin Bai, Weiyang Liu, Guiyou Zhang, Liangcai Jia, Haiyang Li, Li Yu, Yingcui Liao, Mingzhi |
author_sort | Wang, Wenjing |
collection | PubMed |
description | Autophagy is the natural, regulated, destructive mechanism of the eukaryotes cell that disassembles unnecessary or dysfunctional components. In recent years, the association between autophagy and diseases has attracted more and more attention, but our understanding of the molecular mechanism about the association in the system perspective is limited and ambiguous. Hence, we developed the comprehensive bioinformatics resource Autophagy To Disease (ATD, http://auto2disease.nwsuaflmz.com) to archive autophagy-associated diseases. This resource provides bioinformatics annotation system about genes and chemicals about autophagy and human diseases by extracting results from previous studies with text mining technology. Based on the big data from ATD, we found that some classes of disease tend to be related with autophagy, including respiratory disease, cancer, urogenital disease and digestive system disease. We also found that some classes of autophagy-related diseases have a strong association among each other and constitute modules. Furthermore, we extracted the autophagy–disease-related genes (ADGs) from ATD and provided a novel algorithm Optimized Random Forest with Label model to predict potential ADGs. This bioinformatics annotation system about autophagy and human diseases may provide a basic resource for the further detection of the molecular mechanisms of autophagy pathway to disease. |
format | Online Article Text |
id | pubmed-6146119 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-61461192018-09-25 ATD: a comprehensive bioinformatics resource for deciphering the association of autophagy and diseases Wang, Wenjing Zhang, Peng Li, Leijie Chen, Zhaobin Bai, Weiyang Liu, Guiyou Zhang, Liangcai Jia, Haiyang Li, Li Yu, Yingcui Liao, Mingzhi Database (Oxford) Database Tool Autophagy is the natural, regulated, destructive mechanism of the eukaryotes cell that disassembles unnecessary or dysfunctional components. In recent years, the association between autophagy and diseases has attracted more and more attention, but our understanding of the molecular mechanism about the association in the system perspective is limited and ambiguous. Hence, we developed the comprehensive bioinformatics resource Autophagy To Disease (ATD, http://auto2disease.nwsuaflmz.com) to archive autophagy-associated diseases. This resource provides bioinformatics annotation system about genes and chemicals about autophagy and human diseases by extracting results from previous studies with text mining technology. Based on the big data from ATD, we found that some classes of disease tend to be related with autophagy, including respiratory disease, cancer, urogenital disease and digestive system disease. We also found that some classes of autophagy-related diseases have a strong association among each other and constitute modules. Furthermore, we extracted the autophagy–disease-related genes (ADGs) from ATD and provided a novel algorithm Optimized Random Forest with Label model to predict potential ADGs. This bioinformatics annotation system about autophagy and human diseases may provide a basic resource for the further detection of the molecular mechanisms of autophagy pathway to disease. Oxford University Press 2018-09-18 /pmc/articles/PMC6146119/ /pubmed/30239683 http://dx.doi.org/10.1093/database/bay093 Text en © The Author(s) 2018. Published by Oxford University Press. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Tool Wang, Wenjing Zhang, Peng Li, Leijie Chen, Zhaobin Bai, Weiyang Liu, Guiyou Zhang, Liangcai Jia, Haiyang Li, Li Yu, Yingcui Liao, Mingzhi ATD: a comprehensive bioinformatics resource for deciphering the association of autophagy and diseases |
title | ATD: a comprehensive bioinformatics resource for deciphering the association of autophagy and diseases |
title_full | ATD: a comprehensive bioinformatics resource for deciphering the association of autophagy and diseases |
title_fullStr | ATD: a comprehensive bioinformatics resource for deciphering the association of autophagy and diseases |
title_full_unstemmed | ATD: a comprehensive bioinformatics resource for deciphering the association of autophagy and diseases |
title_short | ATD: a comprehensive bioinformatics resource for deciphering the association of autophagy and diseases |
title_sort | atd: a comprehensive bioinformatics resource for deciphering the association of autophagy and diseases |
topic | Database Tool |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6146119/ https://www.ncbi.nlm.nih.gov/pubmed/30239683 http://dx.doi.org/10.1093/database/bay093 |
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