@inproceedings{f4dd0799ae5a43a69197306d851ea0e6,
title = "An algorithm for missing value estimation for DNA microarray data",
abstract = "Gene expression data matrices often contain missing expression values. In this paper, we describe a new algorithm, named improved fixed rank approximation algorithm (IFRAA), for missing values estimations of the large gene expression data matrices. We compare the present algorithm with the two existing and widely used methods for reconstructing missing entries for DNA microarray gene expression data: the Bayesian principal component analysis (BPCA) and the local least squares imputation method (LLS). The three algorithms were applied to four microarray data sets and two synthetic low-rank data matrices. Certain percentages of the elements of these data sets were randomly deleted, and the three algorithms were used to recover them. In conclusion IFRAA appears to be the most reliable and accurate approach for recovering missing DNA microarray gene expression data, or any other noisy data matrices that are effectively low rank.",
keywords = "Bayesian analysis, Gene expression matrix, K-nearest neighbor, Least squares, Missing values imputation, Principal component analysis, Singular value decomposition",
author = "Shmuel Friedland and Amir Niknejad and Mostafa Kaveh and Hossein Zare",
year = "2006",
month = dec,
day = "1",
language = "English (US)",
isbn = "142440469X",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
pages = "II1092--II1095",
booktitle = "2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings",
note = "2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 ; Conference date: 14-05-2006 Through 19-05-2006",
}