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BMCBI
2008
157views more  BMCBI 2008»
13 years 6 months ago
Dimension reduction with redundant gene elimination for tumor classification
Background: Analysis of gene expression data for tumor classification is an important application of bioinformatics methods. But it is hard to analyse gene expression data from DN...
Xue-Qiang Zeng, Guo-Zheng Li, Jack Y. Yang, Mary Q...
DBA
2006
182views Database» more  DBA 2006»
13 years 7 months ago
Matrix Apriori: Speeding Up the Search for Frequent Patterns
This work discusses the problem of generating association rules from a set of transactions in a relational database, taking performance and accuracy of found results as the essent...
Judith Pavón, Sidney Viana, Santiago G&oacu...
JCB
2007
198views more  JCB 2007»
13 years 6 months ago
Bayesian Hierarchical Model for Large-Scale Covariance Matrix Estimation
Many bioinformatics problems can implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy esti...
Dongxiao Zhu, Alfred O. Hero III
BMCBI
2007
215views more  BMCBI 2007»
13 years 6 months ago
Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregres
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
Rainer Opgen-Rhein, Korbinian Strimmer
IDEAL
2000
Springer
13 years 9 months ago
Quantization of Continuous Input Variables for Binary Classification
Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Of...
Michal Skubacz, Jaakko Hollmén