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Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD.

Authors :
Chen, Guocai
Jia, Yuxi
Zhu, Lisha
Li, Ping
Zhang, Lin
Tao, Cui
Jim Zheng, W.
Source :
BMC Medical Informatics & Decision Making. 1/31/2019 Supplement 1, Vol. 19 Issue 1, p1-9. 9p. 4 Diagrams, 1 Chart, 1 Graph.
Publication Year :
2019

Abstract

<bold>Background: </bold>Disease comorbidity is very common and has significant impact on disease treatment. Revealing the associations among diseases may help to understand the mechanisms of diseases, improve the prevention and treatment of diseases, and support the discovery of new drugs or new uses of existing drugs.<bold>Methods: </bold>In this paper, we introduced a mathematical model to represent gene related diseases with a series of associated genes based on the overrepresentation of genes and diseases in PubMed literature. We also illustrated an efficient way to reveal the implicit connections between COPD and other diseases based on this model.<bold>Results: </bold>We applied this approach to analyze the relationships between Chronic Obstructive Pulmonary Disease (COPD) and other diseases under the Lung diseases branch in the Medical subject heading index system and detected 4 novel diseases relevant to COPD. As judged by domain experts, the F score of our approach is up to 77.6%.<bold>Conclusions: </bold>The results demonstrate the effectiveness of the gene fingerprint model for diseases on the basis of medical literature. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14726947
Volume :
19
Issue :
1
Database :
Academic Search Index
Journal :
BMC Medical Informatics & Decision Making
Publication Type :
Academic Journal
Accession number :
134377216
Full Text :
https://doi.org/10.1186/s12911-019-0738-7