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BIODATAMINING
2008
135views more  BIODATAMINING 2008»
13 years 10 months ago
Fast Gene Ontology based clustering for microarray experiments
Background: Analysis of a microarray experiment often results in a list of hundreds of diseaseassociated genes. In order to suggest common biological processes and functions for t...
Kristian Ovaska, Marko Laakso, Sampsa Hautaniemi
BMCBI
2002
195views more  BMCBI 2002»
13 years 10 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, ...
CORR
1999
Springer
222views Education» more  CORR 1999»
13 years 10 months ago
Analysis of approximate nearest neighbor searching with clustered point sets
Abstract. Nearest neighbor searching is a fundamental computational problem. A set of n data points is given in real d-dimensional space, and the problem is to preprocess these poi...
Songrit Maneewongvatana, David M. Mount
ACMSE
2007
ACM
14 years 2 months ago
Verifying design modularity, hierarchy, and interaction locality using data clustering techniques
Modularity, hierarchy, and interaction locality are general approaches to reducing the complexity of any large system. A widely used principle in achieving these goals in designin...
Liguo Yu, Srini Ramaswamy
CORR
2011
Springer
151views Education» more  CORR 2011»
13 years 5 months ago
A supervised clustering approach for fMRI-based inference of brain states
We propose a method that combines signals from many brain regions observed in functional Magnetic Resonance Imaging (fMRI) to predict the subject’s behavior during a scanning se...
Vincent Michel, Alexandre Gramfort, Gaël Varo...