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» Sequential Hierarchical Pattern Clustering
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BMCBI
2006
119views more  BMCBI 2006»
13 years 7 months ago
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs
BMCBI
2004
158views more  BMCBI 2004»
13 years 7 months ago
Incremental genetic K-means algorithm and its application in gene expression data analysis
Background: In recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms suc...
Yi Lu, Shiyong Lu, Farshad Fotouhi, Youping Deng, ...
BMCBI
2007
116views more  BMCBI 2007»
13 years 8 months ago
Ranked Adjusted Rand: integrating distance and partition information in a measure of clustering agreement
Background: Biological information is commonly used to cluster or classify entities of interest such as genes, conditions, species or samples. However, different sources of data c...
Francisco R. Pinto, João A. Carriço,...
BMCBI
2008
115views more  BMCBI 2008»
13 years 8 months ago
Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient
Background: Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson corre...
Jianchao Yao, Chunqi Chang, Mari L. Salmi, Yeung S...
HPDC
2009
IEEE
14 years 2 months ago
Pluggable parallelisation
This paper presents the concept of pluggable parallelisation that allows scientists to develop “sequential like” codes that can take advantage of multi-core, cluster and grid ...
Rui C. Gonçalves, João Luís S...