Katja Ickstadt

TL;DR: In this article, Doubly stochastic Bayesian hierarchical models are introduced to account for uncertainty and spatial variation in the underlying intensity measure for point process models, which are applied to a problem in forest ecology.

TL;DR: TXNRD1 and TXNIP are associated with prognosis in breast cancer, and ERBB2 seems to be one of the factors shifting balances of both factors of the redox control system in a prognostic unfavorable manner.

TL;DR: New criteria for estimating a clustering, which are based on the posterior expected adjusted Rand index, are proposed and are shown to possess a shrinkage property and outperform Binder's loss in a simulation study and in an application to gene expression data.

TL;DR: In this paper, logic regression is used to identify SNP interactions explanatory for the disease status in a case-control study and propose two measures for quantifying the importance of these interactions for classification, which are then applied to the SNP data of the GENICA study, a study dedicated to the identification of genetic and gene-environment interactions associated with sporadic breast cancer.

TL;DR: This paper shows how logic regression can be employed to identify SNP interactions explanatory for the disease status in a case-control study and proposes 2 measures for quantifying the importance of these interactions for classification.