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16 years 8 months ago
Algorithms for Clustering Data
"Cluster analysis is an important technique in the rapidly growing field known as exploratory data analysis and is being applied in a variety of engineering and scientific dis...
A. K. Jain, R. C. Dubes
BMCBI
2010
132views more  BMCBI 2010»
14 years 10 months ago
Data structures and compression algorithms for high-throughput sequencing technologies
Background: High-throughput sequencing (HTS) technologies play important roles in the life sciences by allowing the rapid parallel sequencing of very large numbers of relatively s...
Kenny Daily, Paul Rigor, Scott Christley, Xiaohui ...
GECCO
2007
Springer
197views Optimization» more  GECCO 2007»
15 years 4 months ago
Computational intelligence techniques: a study of scleroderma skin disease
This paper presents an analysis of microarray gene expression data from patients with and without scleroderma skin disease using computational intelligence and visual data mining ...
Julio J. Valdés, Alan J. Barton
BMCBI
2007
168views more  BMCBI 2007»
14 years 10 months ago
GOSim - an R-package for computation of information theoretic GO similarities between terms and gene products
Background: With the increased availability of high throughput data, such as DNA microarray data, researchers are capable of producing large amounts of biological data. During the...
Holger Fröhlich, Nora Speer, Annemarie Poustk...
PR
2006
116views more  PR 2006»
14 years 9 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