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» Clustering cancer gene expression data: a comparative study
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BMCBI
2010
151views more  BMCBI 2010»
15 years 6 months ago
Data reduction for spectral clustering to analyze high throughput flow cytometry data
Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular ...
Habil Zare, Parisa Shooshtari, Arvind Gupta, Ryan ...
CSB
2003
IEEE
106views Bioinformatics» more  CSB 2003»
15 years 11 months ago
Reconstruction of Ancestral Gene Order after Segmental Duplication and Gene Loss
As gene order evolves through a variety of chromosomal rearrangements, conserved segments provide important insight into evolutionary relationships and functional roles of genes. ...
Jun Huan, Jan Prins, Wei Wang 0010, Todd J. Vision
DILS
2005
Springer
15 years 11 months ago
Integrating Heterogeneous Microarray Data Sources Using Correlation Signatures
Abstract. Microarrays are one of the latest breakthroughs in experimental molecular biology. Thousands of different research groups generate tens of thousands of microarray gene e...
Jaewoo Kang, Jiong Yang, Wanhong Xu, Pankaj Chopra
PR
2006
116views more  PR 2006»
15 years 6 months ago
Shared farthest neighbor approach to clustering of high dimensionality, low cardinality data
Clustering algorithms are routinely used in biomedical disciplines, and are a basic tool in bioinformatics. Depending on the task at hand, there are two most popular options, the ...
Stefano Rovetta, Francesco Masulli
BMCBI
2011
14 years 9 months ago
SeqGene: a comprehensive software solution for mining exome- and transcriptome- sequencing data
Background: The popularity of massively parallel exome and transcriptome sequencing projects demands new data mining tools with a comprehensive set of features to support a wide r...
Xutao Deng