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» Two-phase clustering strategy for gene expression data sets
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BMCBI
2008
121views more  BMCBI 2008»
14 years 9 months ago
Stability of gene contributions and identification of outliers in multivariate analysis of microarray data
Background: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages com...
Florent Baty, Daniel Jaeger, Frank Preiswerk, Mart...
BMCBI
2010
139views more  BMCBI 2010»
14 years 9 months ago
A highly efficient multi-core algorithm for clustering extremely large datasets
Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
Johann M. Kraus, Hans A. Kestler
IDA
2006
Springer
14 years 9 months ago
Supporting bi-cluster interpretation in 0/1 data by means of local patterns
Clustering or co-clustering techniques have been proved useful in many application domains. A weakness of these techniques remains the poor support for grouping characterization. ...
Ruggero G. Pensa, Céline Robardet, Jean-Fra...
BMCBI
2006
158views more  BMCBI 2006»
14 years 9 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...
GECCO
2007
Springer
197views Optimization» more  GECCO 2007»
15 years 3 months ago
Computational intelligence techniques: a study of scleroderma skin disease
This paper presents an analysis of microarray gene expression data from patients with and without scleroderma skin disease using computational intelligence and visual data mining ...
Julio J. Valdés, Alan J. Barton