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 | |
发表期刊 | JOURNAL OF BIOLOGICAL SYSTEMS |
2010-09-01 | |
卷号 | 18期号:3页码:605-619 |
文章类型 | Article |
摘要 | Hyperlipidemia (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. |
关键词 | Hyperlipidemia Unstable Angina Biomarker Feature Selection Data Mining |
WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
关键词[WOS] | TRADITIONAL CHINESE MEDICINE ; MUTUAL INFORMATION ; TARGET DISCOVERY |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Life Sciences & Biomedicine - Other Topics ; Mathematical & Computational Biology |
WOS类目 | Biology ; Mathematical & Computational Biology |
WOS记录号 | WOS:000283629300004 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/9727 |
专题 | 综合信息系统研究中心 |
作者单位 | 1.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 |
推荐引用方式 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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