A hybrid imputation approach for microarray missing value estimation
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...
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DNA microarray technology which is used in molecular biology, allows for the observation of expression levels of thousands of genes under a variety of conditions. The analysis of microarray data has been successfully applied in a number of studies over a broad range of biological disciplines. Now it is very unfortunate that various microarray experiments generate data sets containing missing va...
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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: 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...
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ژورنال
عنوان ژورنال: BMC Genomics
سال: 2015
ISSN: 1471-2164
DOI: 10.1186/1471-2164-16-s9-s1