Krämer, Nicole, Schäfer, Juliane, Boulesteix, Anne-Laure
Graphical Gaussian models are popular tools for the estimation of (undirected) gene association networks from microarray data. A key issue when the number of variables greatly exceeds the number of...
Regularized Estimation of Large Scale Gene Regulatory Networks (2008)
Nicole Krämer, Juliane Schäfer, Anne-laure Boulesteix
When dealing with graphical Gaussian models for gene regulatory networks, the major problem is to compute the matrix of partial correlations. Based on the close connection between partial...
On the use of Fractional Polynomials in Dynamic Cox Models (2007)
Ursula Berger, Pia Gerein, Kurt Ulm, Juliane Schäfer
Despite a sophisticated research on modelling of survival data in the last years, the most popular model used in practice is still the proportional hazards regression model proposed by Cox (1972)....
Learning Large-Scale Graphical Gaussian Models from Genomic Data (2005)
Juliane Schäfer, Korbinian Strimmer
The inference and modeling of network-like structures in genomic data is of prime importance in systems biology. Complex stochastic associations and interdependencies can very generally be described...
An empirical Bayes approach to inferring large-scale gene association networks (2005)
Schäfer, Juliane, Strimmer, Korbinian
Motivation: Genetic networks are often described statistically using graphical models (e.g. Bayesian networks). However, inferring the network structure offers a serious challenge in microarray...
An empirical bayes approach to inferring large-scale gene association networks (2004)
Schäfer, Juliane, Strimmer, Korbinian
Motivation: Genetic networks are often described statistically by graphical models (e.g. Bayesian networks). However, inferring the network structure offers a serious challenge in microarray analysis...
An empirical bayes approach to inferring large-scale gene association networks (2004)
Schäfer, Juliane, Strimmer, Korbinian
Motivation: Genetic networks are often described statistically by graphical models (e.g. Bayesian networks). However, inferring the network structure offers a serious challenge in microarray analysis...
On the use of Fractional Polynomials in Dynamic Cox Models (2000)
Berger, Ursula, Gerein, Pia, Ulm, Kurt, Schäfer, Juliane
Despite a sophisticated research on modelling of survival data in the last years, the most popular model used in practice is still the proportional hazards regression model proposed by Cox (1972)....
Lange, Vinzenz, Malmström, Johan A., Didion, John, King, Nichole L., Johansson, Björn P., Schäfer, Juliane, ...
In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially...