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» Clustering cancer gene expression data: a comparative study
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98
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IJON
2008
128views more  IJON 2008»
14 years 11 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
2006
116views more  BMCBI 2006»
14 years 11 months ago
Cluster analysis for DNA methylation profiles having a detection threshold
Background: DNA methylation, a molecular feature used to investigate tumor heterogeneity, can be measured on many genomic regions using the MethyLight technology. Due to the combi...
Paul Marjoram, Jing Chang, Peter W. Laird, Kimberl...
AIME
2009
Springer
15 years 3 months ago
Effect of Background Correction on Cancer Classification with Gene Expression Data
This paper empirically compares six background correction methods aimed at removing unspecific background noise of the overall signal level measured by a scanner across microarrays...
Adelaide Freitas, Gladys Castillo, Ana São ...
112
Voted
BMCBI
2010
123views more  BMCBI 2010»
14 years 11 months ago
Prediction of breast cancer prognosis using gene set statistics provides signature stability and biological context
Background: Different microarray studies have compiled gene lists for predicting outcomes of a range of treatments and diseases. These have produced gene lists that have little ov...
Gad Abraham, Adam Kowalczyk, Sherene Loi, Izhak Ha...
ICONIP
2010
14 years 9 months ago
Exploring Features and Classifiers to Classify MicroRNA Expression Profiles of Human Cancer
Recently, some non-coding small RNAs, known as microRNAs (miRNA), have drawn a lot of attention to identify their role in gene regulation and various biological processes. The miRN...
Kyung-Joong Kim, Sung-Bae Cho