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» Clustering cancer gene expression data: a comparative study
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BMCBI
2008
117views more  BMCBI 2008»
15 years 6 months ago
New resampling method for evaluating stability of clusters
Background: Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in cluste...
Irina Gana Dresen, Tanja Boes, Johannes Hüsin...
COMPLIFE
2005
Springer
15 years 11 months ago
Robust Perron Cluster Analysis for Various Applications in Computational Life Science
In the present paper we explain the basic ideas of Robust Perron Cluster Analysis (PCCA+) and exemplify the different application areas of this new and powerful method. Recently, ...
Marcus Weber, Susanna Kube
BMCBI
2006
94views more  BMCBI 2006»
15 years 6 months ago
Noise-injected neural networks show promise for use on small-sample expression data
Background: Overfitting the data is a salient issue for classifier design in small-sample settings. This is why selecting a classifier from a constrained family of classifiers, on...
Jianping Hua, James Lowey, Zixiang Xiong, Edward R...
MMAS
2010
Springer
15 years 29 days ago
Clustering and Classification through Normalizing Flows in Feature Space
A unified variational methodology is developed for classification and clustering problems, and tested in the classification of tumors from gene expression data. It is based on flu...
J. P. Agnelli, M. Cadeiras, E. G. Tabak, C. V. Tur...
BMCBI
2006
137views more  BMCBI 2006»
15 years 6 months ago
Biologically relevant effects of mRNA amplification on gene expression profiles
Background: Gene expression microarray technology permits the analysis of global gene expression profiles. The amount of sample needed limits the use of small excision biopsies an...
Rachel I. M. van Haaften, Blanche Schroen, Ben J. ...