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Gendoo: Functional profiling of gene and disease features using MeSH vocabulary
Genome-wide data enables us to clarify the underlying molecular mechanisms of complex phenotypes. The Online Mendelian Inheritance in Man (OMIM) is a widely employed knowledge base of human genes and genetic disorders for biological researchers. However, OMIM has not been fully exploited for omics a...
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Formato: | Texto |
Lenguaje: | English |
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Oxford University Press
2009
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2703956/ https://www.ncbi.nlm.nih.gov/pubmed/19498079 http://dx.doi.org/10.1093/nar/gkp483 |
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author | Nakazato, Takeru Bono, Hidemasa Matsuda, Hideo Takagi, Toshihisa |
author_facet | Nakazato, Takeru Bono, Hidemasa Matsuda, Hideo Takagi, Toshihisa |
author_sort | Nakazato, Takeru |
collection | PubMed |
description | Genome-wide data enables us to clarify the underlying molecular mechanisms of complex phenotypes. The Online Mendelian Inheritance in Man (OMIM) is a widely employed knowledge base of human genes and genetic disorders for biological researchers. However, OMIM has not been fully exploited for omics analysis because its bibliographic data structure is not suitable for computer automation. Here, we characterized diseases and genes by generating feature profiles of associated drugs, biological phenomena and anatomy with the MeSH (Medical Subject Headings) vocabulary. We obtained 1 760 054 pairs of OMIM entries and MeSH terms by utilizing the full set of MEDLINE articles. We developed a web-based application called Gendoo (gene, disease features ontology-based overview system) to visualize these profiles. By comparing feature profiles of types 1 and 2 diabetes, we clearly illustrated their differences: type 1 diabetes is an autoimmune disease (P-value = 4.55 × 10(−5)) and type 2 diabetes is related to obesity (P-value = 1.18 × 10(−15)). Gendoo and the developed feature profiles should be useful for omics analysis from molecular and clinical viewpoints. Gendoo is available at http://gendoo.dbcls.jp/. |
format | Text |
id | pubmed-2703956 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-27039562009-07-01 Gendoo: Functional profiling of gene and disease features using MeSH vocabulary Nakazato, Takeru Bono, Hidemasa Matsuda, Hideo Takagi, Toshihisa Nucleic Acids Res Articles Genome-wide data enables us to clarify the underlying molecular mechanisms of complex phenotypes. The Online Mendelian Inheritance in Man (OMIM) is a widely employed knowledge base of human genes and genetic disorders for biological researchers. However, OMIM has not been fully exploited for omics analysis because its bibliographic data structure is not suitable for computer automation. Here, we characterized diseases and genes by generating feature profiles of associated drugs, biological phenomena and anatomy with the MeSH (Medical Subject Headings) vocabulary. We obtained 1 760 054 pairs of OMIM entries and MeSH terms by utilizing the full set of MEDLINE articles. We developed a web-based application called Gendoo (gene, disease features ontology-based overview system) to visualize these profiles. By comparing feature profiles of types 1 and 2 diabetes, we clearly illustrated their differences: type 1 diabetes is an autoimmune disease (P-value = 4.55 × 10(−5)) and type 2 diabetes is related to obesity (P-value = 1.18 × 10(−15)). Gendoo and the developed feature profiles should be useful for omics analysis from molecular and clinical viewpoints. Gendoo is available at http://gendoo.dbcls.jp/. Oxford University Press 2009-07-01 2009-06-04 /pmc/articles/PMC2703956/ /pubmed/19498079 http://dx.doi.org/10.1093/nar/gkp483 Text en © 2009 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Nakazato, Takeru Bono, Hidemasa Matsuda, Hideo Takagi, Toshihisa Gendoo: Functional profiling of gene and disease features using MeSH vocabulary |
title | Gendoo: Functional profiling of gene and disease features using MeSH vocabulary |
title_full | Gendoo: Functional profiling of gene and disease features using MeSH vocabulary |
title_fullStr | Gendoo: Functional profiling of gene and disease features using MeSH vocabulary |
title_full_unstemmed | Gendoo: Functional profiling of gene and disease features using MeSH vocabulary |
title_short | Gendoo: Functional profiling of gene and disease features using MeSH vocabulary |
title_sort | gendoo: functional profiling of gene and disease features using mesh vocabulary |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2703956/ https://www.ncbi.nlm.nih.gov/pubmed/19498079 http://dx.doi.org/10.1093/nar/gkp483 |
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