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» Unfolding of Microarray Data
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ECML
2006
Springer
15 years 1 months ago
Subspace Metric Ensembles for Semi-supervised Clustering of High Dimensional Data
A critical problem in clustering research is the definition of a proper metric to measure distances between points. Semi-supervised clustering uses the information provided by the ...
Bojun Yan, Carlotta Domeniconi
85
Voted
AIME
2005
Springer
15 years 2 days ago
An Algorithm to Learn Causal Relations Between Genes from Steady State Data: Simulation and Its Application to Melanoma Dataset
In recent years, a few researchers have challenged past dogma and suggested methods (such as the IC algorithm) for inferring causal relationship among variables using steady state ...
Xin Zhang, Chitta Baral, Seungchan Kim
80
Voted
PR
2006
116views more  PR 2006»
14 years 10 months ago
Shared farthest neighbor approach to clustering of high dimensionality, low cardinality data
Clustering algorithms are routinely used in biomedical disciplines, and are a basic tool in bioinformatics. Depending on the task at hand, there are two most popular options, the ...
Stefano Rovetta, Francesco Masulli
PRIB
2009
Springer
147views Bioinformatics» more  PRIB 2009»
15 years 4 months ago
Cross-Platform Analysis with Binarized Gene Expression Data
Abstract. With widespread use of microarray technology as a potential diagnostics tool, the comparison of results obtained from the use of different platforms is of interest. When...
Salih Tuna, Mahesan Niranjan
BIBE
2004
IEEE
107views Bioinformatics» more  BIBE 2004»
15 years 1 months ago
Enhanced pClustering and Its Applications to Gene Expression Data
Clustering has been one of the most popular methods to discover useful biological insights from DNA microarray. An interesting paradigm is simultaneous clustering of both genes an...
Sungroh Yoon, Christine Nardini, Luca Benini, Giov...