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» Integrative missing value estimation for microarray data
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BMCBI
2006
116views more  BMCBI 2006»
13 years 7 months ago
Integrative missing value estimation for microarray data
Background: Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performan...
Jianjun Hu, Haifeng Li, Michael S. Waterman, Xiang...
HIS
2004
13 years 9 months ago
K-Ranked Covariance Based Missing Values Estimation for Microarray Data Classification
Microarray data often contains multiple missing genetic expression values that degrade the performance of statistical and machine learning algorithms. This paper presents a K rank...
Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence ...
AINA
2008
IEEE
14 years 2 months ago
Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
Connie Phong, Raul Singh
BMCBI
2006
211views more  BMCBI 2006»
13 years 7 months ago
Missing value estimation for DNA microarray gene expression data by Support Vector Regression imputation and orthogonal coding s
Background: Gene expression profiling has become a useful biological resource in recent years, and it plays an important role in a broad range of areas in biology. The raw gene ex...
Xian Wang, Ao Li, Zhaohui Jiang, Huanqing Feng
BMCBI
2007
149views more  BMCBI 2007»
13 years 7 months ago
Robust imputation method for missing values in microarray data
Background: When analyzing microarray gene expression data, missing values are often encountered. Most multivariate statistical methods proposed for microarray data analysis canno...
Dankyu Yoon, Eun-Kyung Lee, Taesung Park