Network Based Integrated Analysis of Phenotype-Genotype Data for Prioritization of Candidate Symptom Genes
Joint Authors
Jia, Caiyan
Liu, Baoyan
Peng, Yonghong
Zhou, Xuezhong
Yu, Jian
Zhang, Runshun
Hu, Jingqing
Sun, Changkai
Li, Xing
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-02
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Background.
Symptoms and signs (symptoms in brief) are the essential clinical manifestations for individualized diagnosis and treatment in traditional Chinese medicine (TCM).
To gain insights into the molecular mechanism of symptoms, we develop a computational approach to identify the candidate genes of symptoms.
Methods.
This paper presents a network-based approach for the integrated analysis of multiple phenotype-genotype data sources and the prediction of the prioritizing genes for the associated symptoms.
The method first calculates the similarities between symptoms and diseases based on the symptom-disease relationships retrieved from the PubMed bibliographic database.
Then the disease-gene associations and protein-protein interactions are utilized to construct a phenotype-genotype network.
The PRINCE algorithm is finally used to rank the potential genes for the associated symptoms.
Results.
The proposed method gets reliable gene rank list with AUC (area under curve) 0.616 in classification.
Some novel genes like CALCA, ESR1, and MTHFR were predicted to be associated with headache symptoms, which are not recorded in the benchmark data set, but have been reported in recent published literatures.
Conclusions.
Our study demonstrated that by integrating phenotype-genotype relationships into a complex network framework it provides an effective approach to identify candidate genes of symptoms.
American Psychological Association (APA)
Li, Xing& Zhou, Xuezhong& Peng, Yonghong& Liu, Baoyan& Zhang, Runshun& Hu, Jingqing…[et al.]. 2014. Network Based Integrated Analysis of Phenotype-Genotype Data for Prioritization of Candidate Symptom Genes. BioMed Research International،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-472068
Modern Language Association (MLA)
Li, Xing…[et al.]. Network Based Integrated Analysis of Phenotype-Genotype Data for Prioritization of Candidate Symptom Genes. BioMed Research International No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-472068
American Medical Association (AMA)
Li, Xing& Zhou, Xuezhong& Peng, Yonghong& Liu, Baoyan& Zhang, Runshun& Hu, Jingqing…[et al.]. Network Based Integrated Analysis of Phenotype-Genotype Data for Prioritization of Candidate Symptom Genes. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-472068
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-472068