BMC Medical Informatics and Decision Making (Jan 2019)

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

  • Guocai Chen,
  • Yuxi Jia,
  • Lisha Zhu,
  • Ping Li,
  • Lin Zhang,
  • Cui Tao,
  • W. Jim Zheng

DOI
https://doi.org/10.1186/s12911-019-0738-7
Journal volume & issue
Vol. 19, no. S1
pp. 1 – 9

Abstract

Read online

Abstract Background 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. Methods 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. Results 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%. Conclusions The results demonstrate the effectiveness of the gene fingerprint model for diseases on the basis of medical literature.

Keywords