Missing value imputation in DNA microarray gene expression data: a comparative study of an improved collaborative filtering method with decision tree based …
DNA microarray is used to study the expression levels of thousands of genes under various
conditions simultaneously. Unfortunately, microarray experiments can generate datasets …
conditions simultaneously. Unfortunately, microarray experiments can generate datasets …
[PDF][PDF] Missing value estimation in DNA microarrays using B-splines
S Saha, KN Dey, R Dasgupta, A Ghose… - Journal of Medical and …, 2013 - academia.edu
Gene expression profiles generated by the high-throughput microarray experiments are
usually in the form of large matrices with high dimensionality. Unfortunately, microarray …
usually in the form of large matrices with high dimensionality. Unfortunately, microarray …
Missing value estimation in DNA microarrays using linear regression and fuzzy approach
S Saha, PK Singh, KN Dey - Computation and Communication …, 2016 - books.google.com
High-throughput microarray experiments usually generate gene expression profiles in the
form of matrices with high dimensionality. Unfortunately, it may happen that microarray …
form of matrices with high dimensionality. Unfortunately, it may happen that microarray …
An improved fuzzy based approach to impute missing values in DNA microarray gene expression data with collaborative filtering
DNA microarray experiments normally generate gene expression profiles in the form of high
dimensional matrices. It may happen that DNA microarray gene expression values contain …
dimensional matrices. It may happen that DNA microarray gene expression values contain …
An improved fuzzy based missing value estimation in DNA microarray validated by gene ranking
Most of the gene expression data analysis algorithms require the entire gene expression
matrix without any missing values. Hence, it is necessary to devise methods which would …
matrix without any missing values. Hence, it is necessary to devise methods which would …
An ensemble based missing value estimation in DNA microarray using artificial neural network
DNA microarrays are normally used to measure the expression values of thousands of
several genes simultaneously in the form of large matrices. This raw gene expression data …
several genes simultaneously in the form of large matrices. This raw gene expression data …
[PDF][PDF] Research Article An Improved Fuzzy Based Missing Value Estimation in DNA Microarray Validated by Gene Ranking
Most of the gene expression data analysis algorithms require the entire gene expression
matrix without any missing values. Hence, it is necessary to devise methods which would …
matrix without any missing values. Hence, it is necessary to devise methods which would …