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» Additive risk survival model with microarray data
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BMCBI
2006
106views more  BMCBI 2006»
14 years 9 months ago
Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional nor
Background: Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple ...
Henrik Bengtsson, Ola Hössjer
ICICS
2009
Springer
15 years 4 months ago
Assessing Security Risk to a Network Using a Statistical Model of Attacker Community Competence
We propose a novel approach for statistical risk modeling of network attacks that lets an operator perform risk analysis using a data model and an impact model on top of an attack ...
Tomas Olsson
HICSS
2008
IEEE
102views Biometrics» more  HICSS 2008»
15 years 4 months ago
Retrofitting Cyber Physical Systems for Survivability through External Coordination
Most Supervisory Control and Data Acquisition (SCADA) systems have been in operation for decades and they in general have 24x7 availability requirement, hence upgrading or adding ...
Kun Xiao, Shangping Ren, Kevin A. Kwiat
CMSB
2004
Springer
15 years 1 months ago
Residual Bootstrapping and Median Filtering for Robust Estimation of Gene Networks from Microarray Data
We propose a robust estimation method of gene networks based on microarray gene expression data. It is well-known that microarray data contain a large amount of noise and some outl...
Seiya Imoto, Tomoyuki Higuchi, SunYong Kim, Euna J...
ACMICEC
2005
ACM
121views ECommerce» more  ACMICEC 2005»
15 years 3 months ago
A dynamic Bayesian analysis of the drivers of Internet firm survival
We study the impact of a set of industry, firm- and e-commerce-related factors on Internet firm survival. Through the use of one age-based and another calendar time-based Bayesian...
Sudipto Banerjee, Robert J. Kauffman, Bin Wang