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» Using data mining for assessing diagnosis of breast cancer
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BIOINFORMATICS
2006
92views more  BIOINFORMATICS 2006»
13 years 5 months ago
What should be expected from feature selection in small-sample settings
Motivation: High-throughput technologies for rapid measurement of vast numbers of biological variables offer the potential for highly discriminatory diagnosis and prognosis; howev...
Chao Sima, Edward R. Dougherty
BMCBI
2004
97views more  BMCBI 2004»
13 years 5 months ago
Performance of a genetic algorithm for mass spectrometry proteomics
Background: Recently, mass spectrometry data have been mined using a genetic algorithm to produce discriminatory models that distinguish healthy individuals from those with cancer...
Neal O. Jeffries
BMCBI
2005
118views more  BMCBI 2005»
13 years 5 months ago
Feature selection and nearest centroid classification for protein mass spectrometry
Background: The use of mass spectrometry as a proteomics tool is poised to revolutionize early disease diagnosis and biomarker identification. Unfortunately, before standard super...
Ilya Levner
INFOVIS
2003
IEEE
13 years 10 months ago
Exploring High-D Spaces with Multiform Matrices and Small Multiples
We introduce an approach to visual analysis of multivariate data that integrates several methods from information visualization, exploratory data analysis (EDA), and geovisualizat...
Alan M. MacEachren, Xiping Dai, Frank Hardisty, Di...
BMCBI
2008
135views more  BMCBI 2008»
13 years 5 months ago
Identification of a small optimal subset of CpG sites as bio-markers from high-throughput DNA methylation profiles
Background: DNA methylation patterns have been shown to significantly correlate with different tissue types and disease states. High-throughput methylation arrays enable large-sca...
Hailong Meng, Edward Lenn Murrelle, Guoya Li