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BMCBI
2011
14 years 10 months ago
Clustering gene expression data with a penalized graph-based metric
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
Ariel E. Bayá, Pablo M. Granitto
PKDD
2000
Springer
144views Data Mining» more  PKDD 2000»
15 years 10 months ago
Fast Hierarchical Clustering Based on Compressed Data and OPTICS
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
Markus M. Breunig, Hans-Peter Kriegel, Jörg S...
MLDM
2005
Springer
16 years 2 hour ago
Supervised Evaluation of Dataset Partitions: Advantages and Practice
In the context of large databases, data preparation takes a greater importance : instances and explanatory attributes have to be carefully selected. In supervised learning, instanc...
Sylvain Ferrandiz, Marc Boullé
BMCBI
2002
195views more  BMCBI 2002»
15 years 6 months ago
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...
BMCBI
2005
94views more  BMCBI 2005»
15 years 6 months ago
Reproducible Clusters from Microarray Research: Whither?
Motivation: In cluster analysis, the validity of specific solutions, algorithms, and procedures present significant challenges because there is no null hypothesis to test and no &...
Nikhil R. Garge, Grier P. Page, Alan P. Sprague, B...