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» Classes and clusters in data analysis
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KDD
2008
ACM
172views Data Mining» more  KDD 2008»
14 years 10 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
BMCBI
2010
108views more  BMCBI 2010»
13 years 10 months ago
Comparison of scores for bimodality of gene expression distributions and genome-wide evaluation of the prognostic relevance of h
Background: A major goal of the analysis of high-dimensional RNA expression data from tumor tissue is to identify prognostic signatures for discriminating patient subgroups. For t...
Birte Hellwig, Jan G. Hengstler, Marcus Schmidt, M...
CGF
2008
142views more  CGF 2008»
13 years 10 months ago
Visualizing Genome Expression and Regulatory Network Dynamics in Genomic and Metabolic Context
DNA microarrays are used to measure the expression levels of thousands of genes simultaneously. In a time series experiment, the gene expressions are measured as a function of tim...
Michel A. Westenberg, Sacha A. F. T. van Hijum, Os...
IDA
2007
Springer
13 years 10 months ago
Removing biases in unsupervised learning of sequential patterns
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
Yoav Horman, Gal A. Kaminka
NAR
2011
223views Computer Vision» more  NAR 2011»
13 years 25 days ago
ODB: a database for operon organizations, 2011 update
ODB (Operon DataBase) aims to collect data of all known and conserved operons in completely sequenced genomes. Three newly updated features of this database have been added as fol...
Shujiro Okuda, Akiyasu C. Yoshizawa