Paper Info
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.
Year
DOI
Venue
2013
10.1093/database/bas061
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
Keywords
Field
DocType
obesity,database,diabetes mellitus,data mining,software design
Data mining,Diabetes mellitus,Disease,Gene,Candidate gene,Computer science,Identification system,Gene mapping,Obesity,Bioinformatics,Database,Relationship extraction
Journal
Volume
ISSN
Citations 
2013
1758-0463
3
PageRank 
References 
Authors
0.41
8
5
Name
Order
Citations
PageRank
Hong-Jie Dai128821.58
Johnny Chi-Yang Wu2442.30
Richard Tzong-Han Tsai371454.89
Wen-Harn Pan4443.76
Wen-Lian Hsu51701198.40