Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD
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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2019-01-01
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| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12911-019-0738-7 |
| _version_ | 1818116481279328256 |
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| author | Guocai Chen Yuxi Jia Lisha Zhu Ping Li Lin Zhang Cui Tao W. Jim Zheng |
| author_facet | Guocai Chen Yuxi Jia Lisha Zhu Ping Li Lin Zhang Cui Tao W. Jim Zheng |
| author_sort | Guocai Chen |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-11T04:23:12Z |
| format | Article |
| id | doaj.art-4eb02b36eb00487dbaf0208cf07281fa |
| institution | Directory Open Access Journal |
| issn | 1472-6947 |
| language | English |
| last_indexed | 2024-12-11T04:23:12Z |
| publishDate | 2019-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj.art-4eb02b36eb00487dbaf0208cf07281fa2022-12-22T01:21:03ZengBMCBMC Medical Informatics and Decision Making1472-69472019-01-0119S11910.1186/s12911-019-0738-7Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPDGuocai Chen0Yuxi Jia1Lisha Zhu2Ping Li3Lin Zhang4Cui Tao5W. Jim Zheng6School of Biomedical Informatics, University of Texas Health Science Center at HoustonSchool of Biomedical Informatics, University of Texas Health Science Center at HoustonSchool of Biomedical Informatics, University of Texas Health Science Center at HoustonDepartment of Development Pediatrics, The Second Affiliated Hospital of Jilin UniversityDepartment of Respiratory Medicine, The Second Affiliated Hospital of Jilin UniversitySchool of Biomedical Informatics, University of Texas Health Science Center at HoustonSchool of Biomedical Informatics, University of Texas Health Science Center at HoustonAbstract 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.http://link.springer.com/article/10.1186/s12911-019-0738-7Disease connectionGene fingerprint modelChronic obstructive pulmonary diseaseCOPD |
| spellingShingle | Guocai Chen Yuxi Jia Lisha Zhu Ping Li Lin Zhang Cui Tao W. Jim Zheng Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD BMC Medical Informatics and Decision Making Disease connection Gene fingerprint model Chronic obstructive pulmonary disease COPD |
| title | Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD |
| title_full | Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD |
| title_fullStr | Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD |
| title_full_unstemmed | Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD |
| title_short | Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD |
| title_sort | gene fingerprint model for literature based detection of the associations among complex diseases a case study of copd |
| topic | Disease connection Gene fingerprint model Chronic obstructive pulmonary disease COPD |
| url | http://link.springer.com/article/10.1186/s12911-019-0738-7 |
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