title: T-HOD: a literature-based candidate gene database for hypertension, obesity and diabetes.
abstract: Researchers are finding it more and more difficult to follow the changing status of disease candidate genes due to the exponential increase in gene mapping studies. The Text-mined Hypertension, Obesity and Diabetes candidate gene database (T-HOD) is developed to help trace existing research on three kinds of cardiovascular diseases: hypertension, obesity and diabetes, with the last disease categorized into Type 1 and Type 2, by regularly and semiautomatically extracting HOD-related genes from newly published literature. Currently, there are 837, 835 and 821 candidate genes recorded in T-HOD for hypertension, obesity and diabetes, respectively. T-HOD employed the state-of-art text-mining technologies, including a gene/disease identification system and a disease-gene relation extraction system, which can be used to affirm the association of genes with three diseases and provide more evidence for further studies. The primary inputs of T-HOD are the three kinds of diseases, and the output is a list of disease-related genes that can be ranked based on their number of appearance, protein-protein interactions and single-nucleotide polymorphisms. Unlike manually constructed disease gene databases, the content of T-HOD is regularly updated by our text-mining system and verified by domain experts. The interface of T-HOD facilitates easy browsing for users and allows T-HOD curators to verify data efficiently. We believe that T-HOD can help life scientists in search for more disease candidate genes in a less time- and effort-consuming manner. Database URL: http://bws.iis.sinica.edu.tw/THOD.
authors: Intelligent Agent Systems Lab, Institute of Information Science, Academia Sinica, Taipei.
authors: Hong-Jie
authors: HJ
authors: Dai
authors: Johnny Chi-Yang
authors: JC
authors: Wu
authors: Richard Tzong-Han
authors: RT
authors: Tsai
authors: Wen-Harn
authors: WH
authors: Pan
authors: Wen-Lian
authors: WL
authors: Hsu
mesh_terms: D057225:Data Mining; D030541:Databases, Genetic; D003920:Diabetes Mellitus / Q000235:genetics*; D056726:Genetic Association Studies; D020022:Genetic Predisposition to Disease; D006801:Humans; D006973:Hypertension / Q000235:genetics*; D009765:Obesity / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D012985:Software Design; D013223:Statistics as Topic; D014584:User-Computer Interface