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» Analyzing time series gene expression data
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BMCBI
2007
103views more  BMCBI 2007»
13 years 7 months ago
Systems biology approach for mapping the response of human urothelial cells to infection by Enterococcus faecalis
Background: To better understand the response of urinary epithelial (urothelial) cells to Enterococcus faecalis, a uropathogen that exhibits resistance to multiple antibiotics, a ...
Mikhail G. Dozmorov, Kimberly D. Kyker, Ricardo Sa...
CSB
2004
IEEE
136views Bioinformatics» more  CSB 2004»
13 years 11 months ago
Minimum Entropy Clustering and Applications to Gene Expression Analysis
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
Haifeng Li, Keshu Zhang, Tao Jiang
BMCBI
2010
181views more  BMCBI 2010»
13 years 7 months ago
Intensity dependent estimation of noise in microarrays improves detection of differentially expressed genes
Background: In many microarray experiments, analysis is severely hindered by a major difficulty: the small number of samples for which expression data has been measured. When one ...
Amit Zeisel, Amnon Amir, Wolfgang J. Köstler,...
BMCBI
2010
135views more  BMCBI 2010»
13 years 7 months ago
Simple and flexible classification of gene expression microarrays via Swirls and Ripples
Background: A simple classification rule with few genes and parameters is desirable when applying a classification rule to new data. One popular simple classification rule, diagon...
Stuart G. Baker
BMCBI
2006
96views more  BMCBI 2006»
13 years 7 months ago
Bayesian detection of periodic mRNA time profiles without use of training examples
Background: Detection of periodically expressed genes from microarray data without use of known periodic and non-periodic training examples is an important problem, e.g. for ident...
Claes R. Andersson, Anders Isaksson, Mats G. Gusta...