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» Clustering by pattern similarity in large data sets
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BMCBI
2010
153views more  BMCBI 2010»
15 years 6 months ago
Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Eva Freyhult, Mattias Landfors, Jenny Önskog,...
DEXAW
2005
IEEE
96views Database» more  DEXAW 2005»
16 years 4 days ago
Mining Complex Patterns from Protein Surfaces
In the domain of bioinformatics, the role played in the biological process by proteins, that act as transmitters and receivers of information thus ruling the mechanisms that deter...
Lorenzo Baldacci, Matteo Golfarelli
ICDE
2006
IEEE
222views Database» more  ICDE 2006»
16 years 7 months ago
CLAN: An Algorithm for Mining Closed Cliques from Large Dense Graph Databases
Most previously proposed frequent graph mining algorithms are intended to find the complete set of all frequent, closed subgraphs. However, in many cases only a subset of the freq...
Jianyong Wang, Zhiping Zeng, Lizhu Zhou
BMCBI
2007
198views more  BMCBI 2007»
15 years 6 months ago
Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation
Time course gene expression experiments are a popular means to infer co-expression. Many methods have been proposed to cluster genes or to build networks based on similarity measu...
Nicola Neretti, Daniel Remondini, Marc Tatar, John...
ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
16 years 1 months ago
A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks
This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining...
Kanishka Bhaduri, Ashok N. Srivastava