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SELECTING BIOMARKERS FOR PRIMARY HYPERLIPIDEMIA AND UNSTABLE ANGINA IN THE CONTEXT OF NEURO-ENDOCRINE-IMMUNE NETWORK BY FEATURE SELECTION METHODS
Chen, Jianxin2; Jia, Zhenhua1; Wu, Xiangchun1; Yuan, Guoqiang1; Wei, Cong1; Zheng, Chenglong2; Yi, Janqiang3; Wu, Yiling1
Source PublicationJOURNAL OF BIOLOGICAL SYSTEMS
2010-09-01
Volume18Issue:3Pages:605-619
SubtypeArticle
AbstractHyperlipidemia (HL) and unstable angina (UA) are two sequential diseases that cause more and more morbidity and mortality world-wide. Biomarkers selection in the level of physical and chemical specifications (PCS) plays a key role in understanding the pathology of both diseases. Neuro-Endocrine-Immune (NEI) system is a preferable pathway to investigate the interaction network of related PCS in the context of HL, and UA. Data mining approaches are a kind of advanced statistical methods to unravel the "secret" of interaction network of PCS in both diseases. Feature selection methods are a branch of data ruining approaches to select informative subset of PCS as biomarkers to distinguish a disease from healthy control cohort with high classification accuracy. In this paper, we firstly use three feature selection methods combined with decision tree classification algorithm to select several biomarkers from NEI network. The results show that SVM based decision tree is best fit to select biomarkers for both diseases. Furthermore, we use the theory from Traditional Chinese Medicine (TCM) to divide lib and BA patients into two subgroups. Based on this, we propose a. novel feature selection method to distinguish the two subgroups. We combine variance analysis with classification method to select three to four biomarkers for two subgroups in the context of fib and UA respectively, winch means that NEI specifications behave differently between two subgroups. According to basic theory of TCM, variant subgroups defined by TCM need to be treated differently. It means that patients with the same disease may be treated in a personalized way. The research efforts in the paper not only to provide a better avenue to understand the nature of diseases, but also to pave a basis to treat two diseases in a personalized way.
KeywordHyperlipidemia Unstable Angina Biomarker Feature Selection Data Mining
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
WOS KeywordTRADITIONAL CHINESE MEDICINE ; MUTUAL INFORMATION ; TARGET DISCOVERY
Indexed BySCI
Language英语
WOS Research AreaLife Sciences & Biomedicine - Other Topics ; Mathematical & Computational Biology
WOS SubjectBiology ; Mathematical & Computational Biology
WOS IDWOS:000283629300004
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9727
Collection综合信息系统研究中心
Affiliation1.Integrat Tradit & Western Med Res Acad Hebei Prov, Shijiazhuang 050091, Peoples R China
2.Beijing Univ Chinese Med, Beijing 100029, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Chen, Jianxin,Jia, Zhenhua,Wu, Xiangchun,et al. SELECTING BIOMARKERS FOR PRIMARY HYPERLIPIDEMIA AND UNSTABLE ANGINA IN THE CONTEXT OF NEURO-ENDOCRINE-IMMUNE NETWORK BY FEATURE SELECTION METHODS[J]. JOURNAL OF BIOLOGICAL SYSTEMS,2010,18(3):605-619.
APA Chen, Jianxin.,Jia, Zhenhua.,Wu, Xiangchun.,Yuan, Guoqiang.,Wei, Cong.,...&Wu, Yiling.(2010).SELECTING BIOMARKERS FOR PRIMARY HYPERLIPIDEMIA AND UNSTABLE ANGINA IN THE CONTEXT OF NEURO-ENDOCRINE-IMMUNE NETWORK BY FEATURE SELECTION METHODS.JOURNAL OF BIOLOGICAL SYSTEMS,18(3),605-619.
MLA Chen, Jianxin,et al."SELECTING BIOMARKERS FOR PRIMARY HYPERLIPIDEMIA AND UNSTABLE ANGINA IN THE CONTEXT OF NEURO-ENDOCRINE-IMMUNE NETWORK BY FEATURE SELECTION METHODS".JOURNAL OF BIOLOGICAL SYSTEMS 18.3(2010):605-619.
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