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» A cluster validity framework for genome expression data
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107
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ICASSP
2011
IEEE
14 years 7 months ago
Joint modeling of observed inter-arrival times and waveform data with multiple hidden states for neural spike-sorting
We present a novel, maximum likelihood framework for automatic spike-sorting based on a joint statistical model of action potential waveform shape and inter-spike interval duratio...
Brett Matthews, Mark Clements
116
Voted
RECOMB
2002
Springer
16 years 3 months ago
Probabilistic hierarchical clustering for biological data
Biological data, such as gene expression profiles or protein sequences, is often organized in a hierarchy of classes, where the instances assigned to "nearby" classes in...
Eran Segal, Daphne Koller
BMCBI
2005
112views more  BMCBI 2005»
15 years 3 months ago
Visualization methods for statistical analysis of microarray clusters
Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...
Matthew A. Hibbs, Nathaniel C. Dirksen, Kai Li, Ol...
162
Voted
BMCBI
2006
203views more  BMCBI 2006»
15 years 3 months ago
Independent component analysis reveals new and biologically significant structures in micro array data
Background: An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS) problem...
Attila Frigyesi, Srinivas Veerla, David Lindgren, ...
112
Voted
BMCBI
2010
125views more  BMCBI 2010»
15 years 3 months ago
NeatMap - non-clustering heat map alternatives in R
Background: The clustered heat map is the most popular means of visualizing genomic data. It compactly displays a large amount of data in an intuitive format that facilitates the ...
Satwik Rajaram, Yoshi Oono