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» Probabilistic hierarchical clustering for biological data
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BIODATAMINING
2008
96views more  BIODATAMINING 2008»
13 years 8 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
IMSCCS
2006
IEEE
14 years 1 months ago
Clustering of Gene Expression Data: Performance and Similarity Analysis
Background: DNA Microarray technology is an innovative methodology in experimental molecular biology, which has produced huge amounts of valuable data in the profile of gene expre...
Longde Yin, Chun-Hsi Huang
BMCBI
2007
134views more  BMCBI 2007»
13 years 8 months ago
Nearest Neighbor Networks: clustering expression data based on gene neighborhoods
Background: The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both indiv...
Curtis Huttenhower, Avi I. Flamholz, Jessica N. La...
RECOMB
2001
Springer
14 years 8 months ago
Context-specific Bayesian clustering for gene expression data
The recent growth in genomic data and measurements of genome-wide expression patterns allows us to apply computational tools to examine gene regulation by transcription factors. I...
Yoseph Barash, Nir Friedman
BMCBI
2007
177views more  BMCBI 2007»
13 years 7 months ago
The BioPrompt-box: an ontology-based clustering tool for searching in biological databases
Background: High-throughput molecular biology provides new data at an incredible rate, so that the increase in the size of biological databanks is enormous and very rapid. This sc...
Claudio Corsi, Paolo Ferragina, Roberto Marangoni