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» Microarray Gene Expression Data Analysis
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PARMA
2004
136views Database» more  PARMA 2004»
15 years 3 months ago
Using Classification and Visualization on Pattern Databases for Gene Expression Data Analysis
Abstract. We are designing new data mining techniques on gene expression data, more precisely inductive querying techniques that extract a priori interesting bi-sets, i.e., sets of...
Céline Robardet, Ruggero G. Pensa, Jé...
144
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IDA
2006
Springer
15 years 2 months ago
Temporal Bayesian classifiers for modelling muscular dystrophy expression data
The analysis of microarray data from time-series experiments requires specialised algorithms, which take the temporal ordering of the data into account. In this paper we explore a ...
Allan Tucker, Peter A. C. 't Hoen, Veronica Vincio...
BMCBI
2006
158views more  BMCBI 2006»
15 years 2 months ago
Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data
Background: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the p...
Chaoyang Zhang, Peng Li, Arun Rajendran, Youping D...
136
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BIBE
2005
IEEE
15 years 8 months ago
Selecting Informative Genes from Microarray Dataset by Incorporating Gene Ontology
Selecting informative genes from microarray experiments is one of the most important data analysis steps for deciphering biological information imbedded in such experiments. Howev...
Xian Xu, Aidong Zhang
IMSCCS
2006
IEEE
15 years 8 months ago
Estimation Of Cross-Hybridization Signals Using Support Vector Regression
Microarray technology is a powerful biotechnology tool which allows researchers to simultaneously evaluate the expression of thousands of genes, if not the entire expressed genome...
Yijun Sun, Li Liu, Mick Popp, William G. Farmerie