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BMCBI
2005
103views more  BMCBI 2005»
13 years 5 months ago
Quadratic regression analysis for gene discovery and pattern recognition for non-cyclic short time-course microarray experiments
Background: Cluster analyses are used to analyze microarray time-course data for gene discovery and pattern recognition. However, in general, these methods do not take advantage o...
Hua Liu, Sergey Tarima, Aaron S. Borders, Thomas V...
BMCBI
2006
118views more  BMCBI 2006»
13 years 5 months ago
Identification of gene expression patterns using planned linear contrasts
Background: In gene networks, the timing of significant changes in the expression level of each gene may be the most critical information in time course expression profiles. With ...
Hao Li, Constance L. Wood, Yushu Liu, Thomas V. Ge...
BMCBI
2006
157views more  BMCBI 2006»
13 years 5 months ago
Determination of the minimum number of microarray experiments for discovery of gene expression patterns
Background: One type of DNA microarray experiment is discovery of gene expression patterns for a cell line undergoing a biological process over a series of time points. Two import...
Fang-Xiang Wu, W. J. Zhang, Anthony J. Kusalik
IJON
2008
128views more  IJON 2008»
13 years 5 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
2007
139views more  BMCBI 2007»
13 years 5 months ago
Significance analysis of microarray transcript levels in time series experiments
Background: Microarray time series studies are essential to understand the dynamics of molecular events. In order to limit the analysis to those genes that change expression over ...
Barbara Di Camillo, Gianna Toffolo, Sreekumaran K....