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BMCBI
2002
136views more  BMCBI 2002»
13 years 10 months ago
Making sense of EST sequences by CLOBBing them
Background: Expressed sequence tags (ESTs) are single pass reads from randomly selected cDNA clones. They provide a highly cost-effective method to access and identify expressed g...
John Parkinson, David B. Guiliano, Mark L. Blaxter
BMCBI
2010
122views more  BMCBI 2010»
13 years 5 months ago
Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PF
Background: A new paradigm of biological investigation takes advantage of technologies that produce large high throughput datasets, including genome sequences, interactions of pro...
Troy Hawkins, Meghana Chitale, Daisuke Kihara
BIODATAMINING
2008
96views more  BIODATAMINING 2008»
13 years 10 months ago
Fast approximate hierarchical clustering using similarity heuristics
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
Meelis Kull, Jaak Vilo
ICDM
2003
IEEE
111views Data Mining» more  ICDM 2003»
14 years 3 months ago
OP-Cluster: Clustering by Tendency in High Dimensional Space
Clustering is the process of grouping a set of objects into classes of similar objects. Because of unknownness of the hidden patterns in the data sets, the definition of similari...
Jinze Liu, Wei Wang 0010
GECCO
2007
Springer
197views Optimization» more  GECCO 2007»
14 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