Collateral missing value imputation: a new robust missing value estimation algorithm for microarray data
نویسندگان
چکیده
منابع مشابه
BIOINFORMATICS Collateral Missing Value Imputation: A New Robust Missing Value Estimation Algorithm For Microarray Data
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...
متن کاملCollateral missing value imputation: a new robust missing value estimation algorithm for microarray data
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...
متن کاملCollateral Missing Value Estimation: Robust Missing Value Estimation for Consequent Microarray Data Processing
Microarrays have unique ability to probe thousands of genes at a time that makes it a useful tool for variety of applications, ranging from diagnosis to drug discovery. However, data generated by microarrays often contains multiple missing gene expressions that affect the subsequent analysis, as most of the times these missing values are ignored. In this paper we have analyzed how accurate esti...
متن کاملMissing Value Estimation for DNA Microarray Expression Data: Least Squares Imputation
Motivation: Gene expression microarray data sets often contain missing expression values. Robust missing value estimation methods are needed since many algorithms for gene expression analysis require a complete matrix of gene array values. In this paper, imputation methods based on the least squares and cluster structure are proposed to estimate missing values in the gene expression data, which...
متن کاملEvaluation of Missing Value Estimation for Microarray Data
Microarray gene expression data contains missing values (MVs). However, some methods for downstream analyses, including some prediction tools, require a complete expression data matrix. Current methods for estimating the MVs include sample mean and K-nearest neighbors (KNN). Whether the accuracy of estimation (imputation) methods depends on the actual gene expression has not been thoroughly inv...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 2005
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/bti345