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BMCBI
2008
148views more  BMCBI 2008»
13 years 4 months ago
Discovering biclusters in gene expression data based on high-dimensional linear geometries
Background: In DNA microarray experiments, discovering groups of genes that share similar transcriptional characteristics is instrumental in functional annotation, tissue classifi...
Xiangchao Gan, Alan Wee-Chung Liew, Hong Yan
ADAC
2010
110views more  ADAC 2010»
13 years 2 months ago
Robust classification for skewed data
In this paper we propose a robust classification rule for skewed unimodal distributions. For low dimensional data, the classifier is based on minimizing the adjusted outlyingness t...
Mia Hubert, Stephan Van der Veeken
BMCBI
2006
202views more  BMCBI 2006»
13 years 4 months ago
Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks
Background: The learning of global genetic regulatory networks from expression data is a severely under-constrained problem that is aided by reducing the dimensionality of the sea...
David J. Reiss, Nitin S. Baliga, Richard Bonneau
BMCBI
2007
173views more  BMCBI 2007»
13 years 4 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
ICTAI
2007
IEEE
13 years 11 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