A hybrid imputation approach for microarray missing value estimation

BMC Genomics

Volumn 16, Issue 9, 2015, Pages

  Li, Huihui ^a   Zhao, Changbo ^a   Shao, Fengfeng ^a   Li, Guo Zheng ^a,b   Wang, Xiao ^a,c  

^a Tongji University   (China)

^b INSTITUTE OF CHINESE MATERIA MEDICA   (China)

^c ZHENGZHOU UNIVERSITY OF LIGHT INDUSTRY   (China)

Author keywords

Complement strategy; Large missing rate; Microarray gene expression data; Missing value imputation; Normalized root mean squared error

Indexed keywords

ACCURACY; ALGORITHM; ARTICLE; BAYESIAN PRINCIPAL COMPONENT ANALYSIS; CALCULATION; ITERATED LOCAL LEAST SQUARES IMPUTATION; LOCAL LEAST SQUARES; MATHEMATICAL ANALYSIS; NORMALIZED ROOT MEAN SQUARE ERROR; PRINCIPAL COMPONENT ANALYSIS; BAYES THEOREM; DNA MICROARRAY; GENE EXPRESSION PROFILING; HUMAN; LEAST SQUARE ANALYSIS; PROCEDURES; STATISTICAL MODEL;

ALGORITHMS; BAYES THEOREM; GENE EXPRESSION PROFILING; HUMANS; LEAST-SQUARES ANALYSIS; MODELS, STATISTICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS;

EID: 84969580045     PISSN: None     EISSN: 14712164     Source Type: Journal    
DOI: 10.1186/1471-2164-16-S9-S1     Document Type: Article

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