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BMCBI
2004
158views more  BMCBI 2004»
13 years 8 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, ...
KES
2008
Springer
13 years 8 months ago
An Algorithm to Assess the Reliability of Hierarchical Clusters in Gene Expression Data
The validation of clusters discovered in bio-molecular data is a central issue in bioinformatics. Recently, stability-based methods have been successfully applied to the analysis o...
Roberto Avogadri, Matteo Brioschi, Francesca Ruffi...
BMEI
2008
IEEE
13 years 10 months ago
Clustering of High-Dimensional Gene Expression Data with Feature Filtering Methods and Diffusion Maps
The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challen...
Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wun...
NAR
2010
111views more  NAR 2010»
13 years 3 months ago
Babelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional pr
Babelomics is a response to the growing necessity of integrating and analyzing different types of genomic data in an environment that allows an easy functional interpretation of t...
Ignacio Medina, José Carbonell, Luis Pulido...
BMCBI
2005
124views more  BMCBI 2005»
13 years 8 months ago
ErmineJ: Tool for functional analysis of gene expression data sets
Background: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories...
Homin K. Lee, William Braynen, Kiran Keshav, Paul ...