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A combinational feature selection and ensemble neural network method for classification of gene expression data
Liu, B; Cui, QH; Jiang, TZ; Ma, SD
Source PublicationBMC BIOINFORMATICS
2004-09-27
Volume5
SubtypeArticle
AbstractBackground: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for a particular disease. To date, this problem has received most attention in the context of cancer research, especially in tumor classification. Various feature selection methods and classifier design strategies also have been generally used and compared. However, most published articles on tumor classification have applied a certain technique to a certain dataset, and recently several researchers compared these techniques based on several public datasets. But, it has been verified that differently selected features reflect different aspects of the dataset and some selected features can obtain better solutions on some certain problems. At the same time, faced with a large amount of microarray data with little knowledge, it is difficult to find the intrinsic characteristics using traditional methods. In this paper, we attempt to introduce a combinational feature selection method in conjunction with ensemble neural networks to generally improve the accuracy and robustness of sample classification.
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
WOS KeywordSINGULAR-VALUE DECOMPOSITION ; MICROARRAY DATA ; CLUSTER-ANALYSIS ; CANCER ; PREDICTION ; PATTERNS ; DISCOVERY ; TUMOR ; LEUKEMIA ; CYCLE
Indexed BySCI
Language英语
WOS Research AreaBiochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology
WOS SubjectBiochemical Research Methods ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology
WOS IDWOS:000224939900001
Citation statistics
Cited Times:71[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/7976
Collection脑网络组研究中心
AffiliationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Liu, B,Cui, QH,Jiang, TZ,et al. A combinational feature selection and ensemble neural network method for classification of gene expression data[J]. BMC BIOINFORMATICS,2004,5.
APA Liu, B,Cui, QH,Jiang, TZ,&Ma, SD.(2004).A combinational feature selection and ensemble neural network method for classification of gene expression data.BMC BIOINFORMATICS,5.
MLA Liu, B,et al."A combinational feature selection and ensemble neural network method for classification of gene expression data".BMC BIOINFORMATICS 5(2004).
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