Shrinkage regression-based methods for microarray missing value imputation
نویسندگان
چکیده
منابع مشابه
Performance Evaluation of L1-norm-based Microarray Missing Value Imputation
l1-norm minimization was utilized in the imputation of microarray missing values, which is an important procedure in bioinformatics experiments. Two l1 approaches, based on the framework of local least squares (LLS) and iterative biclusterbased least squares (bicluster-iLLS) respectively, were employed. Imputed datasets of the l1 approaches were compared with those of traditional l2 methods. Th...
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Microarray experiments often generate data sets with multiple missing expression values. Estimating these missing values is very important since they affect biological applications and many multivariate statistical analyses. A limitation of the existing estimating methods is that they assume the relations between genes to be linear. However, that is not always the case. In this paper, we propos...
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Motivation: Microarray data is used in a range of application areas in biology, though often it contains considerable numbers of missing values. These missing values can significantly affect subsequent statistical analysis and machine learning algorithms so there is a strong motivation to estimate these values as accurately as possible prior to using these algorithms. While many imputation algo...
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MOTIVATION Microarray data are used in a range of application areas in biology, although often it contains considerable numbers of missing values. These missing values can significantly affect subsequent statistical analysis and machine learning algorithms so there is a strong motivation to estimate these values as accurately as possible before using these algorithms. While many imputation algo...
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Microarray gene expression data often contains missing values resulted from various reasons. However, most of the gene expression data analysis algorithms, such as clustering, classification and network design, require complete information, that is, without any missing values. It is therefore very important to accurately impute the missing values before applying the data analysis algorithms. In...
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ژورنال
عنوان ژورنال: BMC Systems Biology
سال: 2013
ISSN: 1752-0509
DOI: 10.1186/1752-0509-7-s6-s11