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ISNN
2005
Springer
14 years 29 days ago
Non-parametric Statistical Tests for Informative Gene Selection
This paper presents two non-parametric statistical test methods, called Kolmogorov-Smirnov (KS) and U statistic test methods, respectively, for informative gene selection of a tumo...
Jinwen Ma, Fuhai Li, Jianfeng Liu
GCB
2010
Springer
204views Biometrics» more  GCB 2010»
13 years 5 months ago
Learning Pathway-based Decision Rules to Classify Microarray Cancer Samples
: Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninfor...
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasn...
APBC
2003
128views Bioinformatics» more  APBC 2003»
13 years 8 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won
BMCBI
2007
117views more  BMCBI 2007»
13 years 7 months ago
Meta-analysis of several gene lists for distinct types of cancer: A simple way to reveal common prognostic markers
Background: Although prognostic biomarkers specific for particular cancers have been discovered, microarray analysis of gene expression profiles, supported by integrative analysis...
Xinan Yang, Xiao Sun
BMCBI
2008
202views more  BMCBI 2008»
13 years 7 months ago
Network motif-based identification of transcription factor-target gene relationships by integrating multi-source biological data
Background: Integrating data from multiple global assays and curated databases is essential to understand the spatiotemporal interactions within cells. Different experiments measu...
Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Ro...