DocumentCode :
2519423
Title :
Seeking Potential Biological Network Shared in Rheumatoid Arthritis and Ulcerative Colitis through Text Mining
Author :
Ding, Xiaorong ; Zha, Qinglin ; Lu, Aiping
Author_Institution :
Inst. of Basic Res. In Clinical Med., China Acad. of Chinese Med. Sci., Beijing, China
fYear :
2009
fDate :
11-13 June 2009
Firstpage :
1
Lastpage :
3
Abstract :
In traditional Chinese medicine, different diseases might be treated with the same therapy if they show the same pattern, which suggests that these different diseases could have the similar biological pathway or network in some specific fields. Rheumatoid arthritis (RA) and ulcerative colitis (UC) were taken for the potential shared biological network exploration with data mining approach. Text mining tool was applied to analyze the PubMed literature database and integrate the available biological information to seeking the potential biological network shared in RA and UC. The results show that RA and UC have immune and metabolically shared network obtained from analysis on the PubMed database with text mining. It could be concluded that the text mining could be used to explore the potentially biological network shared by different diseases, which further help for leading some new findings in human or animal study.
Keywords :
data mining; database management systems; diseases; medical information systems; orthopaedics; patient treatment; PubMed database; biological network sharing; biological pathway; data mining; disease therapy; diseases; rheumatoid arthritis; text mining; traditional Chinese medicine; ulcerative colitis; Animals; Arthritis; Data mining; Databases; Diseases; Humans; Immune system; Information analysis; Medical treatment; Text mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2901-1
Electronic_ISBN :
978-1-4244-2902-8
Type :
conf
DOI :
10.1109/ICBBE.2009.5163368
Filename :
5163368
Link To Document :
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