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» Evaluation of clustering algorithms for gene expression data
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BMCBI
2005
78views more  BMCBI 2005»
15 years 6 months ago
Correlation test to assess low-level processing of high-density oligonucleotide microarray data
Background: There are currently a number of competing techniques for low-level processing of oligonucleotide array data. The choice of technique has a profound effect on subsequen...
Alexander Ploner, Lance D. Miller, Per Hall, Jonas...
BMCBI
2006
107views more  BMCBI 2006»
15 years 6 months ago
Evaluation of methods for oligonucleotide array data via quantitative real-time PCR
Background: There are currently many different methods for processing and summarizing probelevel data from Affymetrix oligonucleotide arrays. It is of great interest to validate t...
Li-Xuan Qin, Richard P. Beyer, Francesca N. Hudson...
ICPR
2006
IEEE
16 years 7 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen
IDA
2005
Springer
15 years 11 months ago
Bayesian Networks Learning for Gene Expression Datasets
DNA arrays yield a global view of gene expression and can be used to build genetic networks models, in order to study relations between genes. Literature proposes Bayesian network ...
Giacomo Gamberoni, Evelina Lamma, Fabrizio Riguzzi...
BMCBI
2006
198views more  BMCBI 2006»
15 years 6 months ago
Gene selection and classification of microarray data using random forest
Background: Selection of relevant genes for sample classification is a common task in most gene expression studies, where researchers try to identify the smallest possible set of ...
Ramón Díaz-Uriarte, Sara Alvarez de ...