The Correlation-Base-Selection Algorithm for Diagnostic Schizophrenia Based on Blood-Based Gene Expression Signatures
Joint Authors
Zhang, Bao
Zhang, Hang
Xie, Ziyang
Yang, Yuwen
Zhao, Yizhen
Fang, Jing
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-02-09
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Microarray analysis of gene expression is often used to diagnose different types of disease.
Many studies report remarkable achievements in nervous system disease.
Clinical diagnosis of schizophrenia (SCZ) still depends on doctors’ experience, which is unreliable and needs to be more objective and quantified.
To solve this problem, we collected whole blood gene expression data from four studies, including 152 individuals with schizophrenia (SCZ) and 138 normal controls in different regions.
The correlation-based feature selection (CFS, one of the machine learning methods) algorithm was applied in this study, and 103 significantly differentially expressed genes between patients and controls, called “feature genes,” were selected; then, a model for SCZ diagnosis was built.
The samples were subdivided into 10 groups, and cross-validation showed that the model we constructed achieved nearly 100% classification accuracy.
Mathematical evaluation of the datasets before and after data processing proved the effectiveness of our algorithm.
Feature genes were enriched in Parkinson’s disease, oxidative phosphorylation, and TGF-beta signaling pathways, which were previously reported to be associated with SCZ.
These results suggest that the analysis of gene expression in whole blood by our model could be a useful tool for diagnosing SCZ.
American Psychological Association (APA)
Zhang, Hang& Xie, Ziyang& Yang, Yuwen& Zhao, Yizhen& Zhang, Bao& Fang, Jing. 2017. The Correlation-Base-Selection Algorithm for Diagnostic Schizophrenia Based on Blood-Based Gene Expression Signatures. BioMed Research International،Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1138754
Modern Language Association (MLA)
Zhang, Hang…[et al.]. The Correlation-Base-Selection Algorithm for Diagnostic Schizophrenia Based on Blood-Based Gene Expression Signatures. BioMed Research International No. 2017 (2017), pp.1-7.
https://search.emarefa.net/detail/BIM-1138754
American Medical Association (AMA)
Zhang, Hang& Xie, Ziyang& Yang, Yuwen& Zhao, Yizhen& Zhang, Bao& Fang, Jing. The Correlation-Base-Selection Algorithm for Diagnostic Schizophrenia Based on Blood-Based Gene Expression Signatures. BioMed Research International. 2017. Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1138754
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1138754