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» Evaluation of clustering algorithms for gene expression data
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PR
2007
100views more  PR 2007»
15 years 6 months ago
Linear manifold clustering in high dimensional spaces by stochastic search
Classical clustering algorithms are based on the concept that a cluster center is a single point. Clusters which are not compact around a single point are not candidates for class...
Robert M. Haralick, Rave Harpaz
ESWS
2008
Springer
15 years 8 months ago
Instance Based Clustering of Semantic Web Resources
Abstract. The original Semantic Web vision was explicit in the need for intelligent autonomous agents that would represent users and help them navigate the Semantic Web. We argue t...
Gunnar Aastrand Grimnes, Peter Edwards, Alun D. Pr...
BMCBI
2010
96views more  BMCBI 2010»
15 years 6 months ago
ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data
Background: Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-seq) or ChIP followed by genome tiling array analysis (ChIP-chip) have become standar...
Lihua J. Zhu, Claude Gazin, Nathan D. Lawson, Herv...
ICML
2005
IEEE
16 years 7 months ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani
BMCBI
2007
103views more  BMCBI 2007»
15 years 6 months ago
A comprehensive evaluation of SAM, the SAM R-package and a simple modification to improve its performance
Background: The Significance Analysis of Microarrays (SAM) is a popular method for detecting significantly expressed genes and controlling the false discovery rate (FDR). Recently...
Shunpu Zhang