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KDD
2005
ACM
130views Data Mining» more  KDD 2005»
14 years 5 months ago
Simple and effective visual models for gene expression cancer diagnostics
In the paper we show that diagnostic classes in cancer gene expression data sets, which most often include thousands of features (genes), may be effectively separated with simple ...
Gregor Leban, Minca Mramor, Ivan Bratko, Blaz Zupa...
BMCBI
2004
180views more  BMCBI 2004»
13 years 4 months ago
Noise filtering and nonparametric analysis of microarray data underscores discriminating markers of oral, prostate, lung, ovaria
Background: A major goal of cancer research is to identify discrete biomarkers that specifically characterize a given malignancy. These markers are useful in diagnosis, may identi...
Virginie M. Aris, Michael J. Cody, Jeff Cheng, Jam...
BMCBI
2007
149views more  BMCBI 2007»
13 years 4 months ago
Novel and simple transformation algorithm for combining microarray data sets
Background: With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Suc...
Ki-Yeol Kim, Dong Hyuk Ki, Ha Jin Jeong, Hei-Cheul...
AINA
2008
IEEE
13 years 11 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
ESANN
2008
13 years 6 months ago
A method for robust variable selection with significance assessment
Our goal is proposing an unbiased framework for gene expression analysis based on variable selection combined with a significance assessment step. We start by discussing the need ...
Annalisa Barla, Sofia Mosci, Lorenzo Rosasco, Ales...