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» Two-phase clustering strategy for gene expression data sets
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GCB
2003
Springer
105views Biometrics» more  GCB 2003»
15 years 2 months ago
In silico prediction of UTR repeats using clustered EST data
Clustering of EST data is a method for the non-redundant representation of an organisms transcriptome. During clustering of large amounts of EST data, usually some large clusters ...
Stefan A. Rensing, Daniel Lang, Ralf Reski
BMCBI
2005
110views more  BMCBI 2005»
14 years 9 months ago
Considerations when using the significance analysis of microarrays (SAM) algorithm
Background: Users of microarray technology typically strive to use universally acceptable data analysis strategies to determine significant expression changes in their experiments...
Ola Larsson, Claes Wahlestedt, James A. Timmons
MMAS
2010
Springer
14 years 4 months 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...
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
15 years 10 months ago
A framework for ontology-driven subspace clustering
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...
Jinze Liu, Wei Wang 0010, Jiong Yang
IPPS
2002
IEEE
15 years 2 months ago
Parallel EST Clustering
Expressed sequence tags, abbreviated ESTs, are DNA fragments experimentally derived from expressed portions of genes. Clustering of ESTs is essential for gene recognition and unde...
Anantharaman Kalyanaraman, Srinivas Aluru, Suresh ...