Getting started in text mining to find the biological network shared with rheumatoid arthritis, coronary heart disease and diabetes mellitus

Author

Ding, Xiaorong ; Lu, Aiping ; Zha, Qinglin

Author_Institution

Inst. of Basic Res. In Clinical Med., China Acad. of Chinese Med. Sci., Beijing, China

fYear

2010

fDate

18-18 Dec. 2010

Firstpage

609

Lastpage

612

Abstract

In order to contribute to biomedical text extraction and mining in the field of modern research of pattern in traditional Chinese medicine (TCM), MeSH mining method was used in this study. Based on “Different diseases with same pattern” theory in TCM, rheumatoid arthritis, coronary heart disease and diabetes mellitus were selected to explore the potential biological network shared in these three diseases. By means of association analysis method, four main network were presented including oxidation reduction, apoptosis, vascularization and sex hormone. It suggested that text mining could be the starting for the modern research on pattern in TCM.

Keywords

data mining; diseases; medical computing; text analysis; MeSH mining method; TCM; apoptosis; association analysis method; biological network; biomedical text extraction; biomedical text mining; coronary heart disease; diabetes mellitus; oxidation reduction; rheumatoid arthritis; sex hormone; traditional Chinese medicine; vascularization; MeSH; coronary heart disease; diabetes mellitus; pattern; rheumatoid arthritis; text mining;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedicine Workshops (BIBMW), 2010 IEEE International Conference on

Conference_Location

Hong, Kong

Print_ISBN

978-1-4244-8303-7

Electronic_ISBN

978-1-4244-8304-4

Type

conf

DOI

10.1109/BIBMW.2010.5703870

Filename

5703870