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» Clustering gene expression patterns
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BMCBI
2004
205views more  BMCBI 2004»
14 years 9 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
JCB
2007
130views more  JCB 2007»
14 years 9 months ago
Bayesian Inference of MicroRNA Targets from Sequence and Expression Data
MicroRNAs (miRNAs) regulate a large proportion of mammalian genes by hybridizing to targeted messenger RNAs (mRNAs) and down-regulating their translation into protein. Although mu...
Jim C. Huang, Quaid Morris, Brendan J. Frey
PR
2006
119views more  PR 2006»
14 years 9 months ago
Fuzzy Bayesian validation for cluster analysis of yeast cell-cycle data
Clustering for the analysis of the genes organizes the patterns into groups by the similarity of the dataset and has been used for identifying the functions of the genes in the cl...
Sung-Bae Cho, Si-Ho Yoo
BMCBI
2010
148views more  BMCBI 2010»
14 years 10 months ago
Applying unmixing to gene expression data for tumor phylogeny inference
Background: While in principle a seemingly infinite variety of combinations of mutations could result in tumor development, in practice it appears that most human cancers fall int...
Russell Schwartz, Stanley Shackney
BMCBI
2008
117views more  BMCBI 2008»
14 years 10 months ago
New resampling method for evaluating stability of clusters
Background: Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in cluste...
Irina Gana Dresen, Tanja Boes, Johannes Hüsin...