Walter L. Ruzzo

TL;DR: A model of protection mechanisms in computing systems is presented and its appropriateness is argued and it can be shown that this problem is decidable, i.e. there is an algorithm to determine whether a system in a particular configuration is safe.

TL;DR: The empirical study showed that clustering with the PCs instead of the original variables does not necessarily improve, and often degrades, cluster quality, and would not recommend PCA before clustering except in special circumstances.

TL;DR: The model-based approach has superior performance on synthetic data sets, consistently selecting the correct model and the number of clusters, and the validity of the Gaussian mixture assumption on different transformations of real data is explored.

TL;DR: The T. thermophila genome has been used for functional genomic studies to address biological, biomedical, and biotechnological questions of fundamental importance as mentioned in this paper, and it has been shown that the excision of DNA from the MIC to generate the macronucleus specifically targets foreign DNA as a form of genome self-defense.

TL;DR: This work provides a systematic framework for assessing the results of clustering algorithms for gene expression data sets by applying a clustering algorithm to the data from all but one experimental condition.