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» E-CAST: A Data Mining Algorithm for Gene Expression Data
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ICPR
2006
IEEE
14 years 8 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen
PARMA
2004
136views Database» more  PARMA 2004»
13 years 9 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...
BIBE
2007
IEEE
195views Bioinformatics» more  BIBE 2007»
14 years 2 months ago
Finding Clusters of Positive and Negative Coregulated Genes in Gene Expression Data
— In this paper, we propose a system for finding partial positive and negative coregulated gene clusters in microarray data. Genes are clustered together if they show the same p...
Kerstin Koch, Stefan Schönauer, Ivy Jansen, J...
BMCBI
2008
126views more  BMCBI 2008»
13 years 7 months ago
GeneChaser: Identifying all biological and clinical conditions in which genes of interest are differentially expressed
Background: The amount of gene expression data in the public repositories, such as NCBI Gene Expression Omnibus (GEO) has grown exponentially, and provides a gold mine for bioinfo...
Rong Chen, Rohan Mallelwar, Ajit Thosar, Shivkumar...
WILF
2005
Springer
112views Fuzzy Logic» more  WILF 2005»
14 years 1 months ago
NEC for Gene Expression Analysis
Aim of this work is to apply a novel comprehensive machine learning tool for data mining to preprocessing and interpretation of gene expression data. Furthermore, some visualizatio...
Roberto Amato, Angelo Ciaramella, N. Deniskina, Ca...