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Nucleic Acids Research Advance Access published online on June 4, 2009
Nucleic Acids Research, doi:10.1093/nar/gkp483
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© 2009 The Author(s)
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.

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Gendoo: Functional profiling of gene and disease features using MeSH vocabulary

Takeru Nakazato1,2,*, Hidemasa Bono1, Hideo Matsuda2 and Toshihisa Takagi1

1Database Center for Life Science (DBCLS), Research Organization of Information and Systems (ROIS), Faculty of Engineering Building 12, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo 113-0032 and 2Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka 560-8531, Japan

*To whom correspondence should be addressed. Tel: +81 3 5841 6754; Fax: +81 3 5841 8090; Email: nakazato{at}dbcls.rois.ac.jp

Received February 15, 2009. Revised April 27, 2009. Accepted May 19, 2009.

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 x 10–5) and type 2 diabetes is related to obesity (P-value = 1.18 x 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/.


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