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» E-CAST: A Data Mining Algorithm for Gene Expression Data
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BMCBI
2008
105views more  BMCBI 2008»
13 years 7 months ago
A gene pattern mining algorithm using interchangeable gene sets for prokaryotes
Background: Mining gene patterns that are common to multiple genomes is an important biological problem, which can lead us to novel biological insights. When family classification...
Meng Hu, Kwangmin Choi, Wei Su, Sun Kim, Jiong Yan...
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
14 years 1 months ago
A multi-objective approach to discover biclusters in microarray data
The main motivation for using a multi–objective evolutionary algorithm for finding biclusters in gene expression data is motivated by the fact that when looking for biclusters ...
Federico Divina, Jesús S. Aguilar-Ruiz
JBI
2004
171views Bioinformatics» more  JBI 2004»
13 years 9 months ago
Consensus Clustering and Functional Interpretation of Gene Expression Data
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus s...
Paul Kellam, Stephen Swift, Allan Tucker, Veronica...
ICTAI
2007
IEEE
14 years 2 months ago
Accurate Classification of SAGE Data Based on Frequent Patterns of Gene Expression
In this paper we present a method for classifying accurately SAGE (Serial Analysis of Gene Expression) data. The high dimensionality of the data, namely the large number of featur...
George Tzanis, Ioannis P. Vlahavas
NIPS
2003
13 years 9 months ago
ICA-based Clustering of Genes from Microarray Expression Data
We propose an unsupervised methodology using independent component analysis (ICA) to cluster genes from DNA microarray data. Based on an ICA mixture model of genomic expression pa...
Su-In Lee, Serafim Batzoglou