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» Unbiased pattern detection in microarray data series
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BMCBI
2002
195views more  BMCBI 2002»
14 years 9 months ago
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...
EDBT
2004
ACM
110views Database» more  EDBT 2004»
15 years 9 months ago
Using Convolution to Mine Obscure Periodic Patterns in One Pass
The mining of periodic patterns in time series databases is an interesting data mining problem that can be envisioned as a tool for forecasting and predicting the future behavior o...
Mohamed G. Elfeky, Walid G. Aref, Ahmed K. Elmagar...
BMCBI
2008
190views more  BMCBI 2008»
14 years 9 months ago
Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes
Background: Gene expression data frequently contain missing values, however, most downstream analyses for microarray experiments require complete data. In the literature many meth...
Guy N. Brock, John R. Shaffer, Richard E. Blakesle...
BMCBI
2006
118views more  BMCBI 2006»
14 years 9 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...
ICDM
2007
IEEE
196views Data Mining» more  ICDM 2007»
15 years 4 months ago
Diagnosing Similarity of Oscillation Trends in Time Series
Sensor networks have increased the amount and variety of temporal data available, requiring the definition of new techniques for data mining. Related research typically addresses...
Leonardo E. Mariote, Claudia Bauzer Medeiros, Rica...