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» Combined Gene Selection Methods for Microarray Data Analysis
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IJON
2008
128views more  IJON 2008»
15 years 3 months ago
Independent arrays or independent time courses for gene expression time series data analysis
In this paper we apply three different independent component analysis (ICA) methods, including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA), to gene exp...
Sookjeong Kim, Jong Kyoung Kim, Seungjin Choi
BMCBI
2008
179views more  BMCBI 2008»
15 years 3 months ago
Building pathway clusters from Random Forests classification using class votes
Background: Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bri...
Herbert Pang, Hongyu Zhao
BIOINFORMATICS
2007
195views more  BIOINFORMATICS 2007»
15 years 3 months ago
Context-dependent clustering for dynamic cellular state modeling of microarray gene expression
Motivation: High-throughput expression profiling allows researchers to study gene activities globally. Genes with similar expression profiles are likely to encode proteins that ma...
Shinsheng Yuan, Ker-Chau Li
ACSC
2005
IEEE
15 years 8 months ago
Integer Programming Models and Algorithms for Molecular Classification of Cancer from Microarray Data
Novel, high-throughput technologies are challenging the core of algorithmic methods available in Computer Science. Microarray technologies give Life Sciences researchers the oppor...
Regina Berretta, Alexandre Mendes, Pablo Moscato
BMCBI
2005
101views more  BMCBI 2005»
15 years 3 months ago
MASQOT: a method for cDNA microarray spot quality control
Background: cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying ...
Max Bylesjö, Daniel Eriksson, Andreas Sjö...