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» A Repulsive Clustering Algorithm for Gene Expression Data
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ICANN
2005
Springer
14 years 1 months ago
High-Throughput Multi-dimensional Scaling (HiT-MDS) for cDNA-Array Expression Data
Multidimensional Scaling (MDS) is a powerful dimension reduction technique for embedding high-dimensional data into a lowdimensional target space. Thereby, the distance relationshi...
Marc Strickert, Stefan Teichmann, Nese Sreenivasul...
IPPS
2003
IEEE
14 years 1 months ago
Gene Clustering Using Self-Organizing Maps and Particle Swarm Optimization
Gene clustering, the process of grouping related genes in the same cluster, is at the foundation of different genomic studies that aim at analyzing the function of genes. Microarr...
Xiang Xiao, Ernst R. Dow, Russell C. Eberhart, Zin...
WOB
2007
116views Bioinformatics» more  WOB 2007»
13 years 8 months ago
Validating Gene Clusterings by Selecting Informative Gene Ontology Terms with Mutual Information
Abstract. We propose a method for global validation of gene clusterings. The method selects a set of informative and non-redundant GO terms through an exploration of the Gene Ontol...
Ivan G. Costa, Marcílio Carlos Pereira de S...
CIBB
2008
13 years 9 months ago
Mining Association Rule Bases from Integrated Genomic Data and Annotations
During the last decade, several clustering and association rule mining techniques have been applied to highlight groups of coregulated genes in gene expression data. Nowadays, inte...
Ricardo Martínez, Nicolas Pasquier, Claude ...
BIODATAMINING
2008
178views more  BIODATAMINING 2008»
13 years 7 months ago
Clustering-based approaches to SAGE data mining
Serial analysis of gene expression (SAGE) is one of the most powerful tools for global gene expression profiling. It has led to several biological discoveries and biomedical appli...
Haiying Wang, Huiru Zheng, Francisco Azuaje