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CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
14 years 1 months ago
Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network
We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network con...
Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Abur...
BMCBI
2006
115views more  BMCBI 2006»
13 years 8 months ago
Multivariate curve resolution of time course microarray data
Background: Modeling of gene expression data from time course experiments often involves the use of linear models such as those obtained from principal component analysis (PCA), i...
Peter D. Wentzell, Tobias K. Karakach, Sushmita Ro...
JOT
2007
124views more  JOT 2007»
13 years 8 months ago
Displaying Updated Stock Quotes
This paper describes how to extract stock quote data and display it with a dynamic update (using free, but delayed data streams). As a part of the architecture of the program, we ...
Douglas Lyon
BMCBI
2008
87views more  BMCBI 2008»
13 years 9 months ago
Volume-based solvation models out-perform area-based models in combined studies of wild-type and mutated protein-protein interfa
Background: Empirical binding models have previously been investigated for the energetics of protein complexation (G models) and for the influence of mutations on complexation (i....
Salim Bougouffa, Jim Warwicker
BMCBI
2011
13 years 3 months ago
Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
Kyle C. Chipman, Ambuj K. Singh