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Variability in induced pluripotent stem cell (iPSC) lines remains a concern for disease modeling and regenerative medicine. We have used RNA-sequencing analysis and linear mixed models to examine the sources of gene expression variability in 317 human iPSC lines from 101 individuals. We found that ∼50% of genome-wide expression variability is explained by(More)
The insider threat has long been considered one of the most serious threats in computer security, and one of the most difficult to combat. But the problem has never been defined precisely, and that lack of precise definition inhibits solutions. This paper presents a precise definition of insider threat, and shows how the definition enables an analysis of(More)
Network protocols continue to suffer from well documented vulnerabilities. Despite this, a practical methodology for classifying these vulnerabilities does not exist. In this paper, we present such a methodology. We have developed a grammar for expressing network protocol exploits in terms of vulnerabilities and symptoms. Vulnerabilities are defined by(More)
In recent years, the development of programmable graphics pipelines has placed the power of parallel computation in the hands of consumers. Systems developers are now paying attention to the general purpose computational ability of these graphics processor units, or GPUs, and are using them in novel ways. This paper examines using pixel shaders for(More)
Discriminating the gene target of a distal regulatory element from other nearby transcribed genes is a challenging problem with the potential to illuminate the causal underpinnings of complex diseases. We present TargetFinder, a computational method that reconstructs regulatory landscapes from diverse features along the genome. The resulting models(More)
Recent surveys indicate that the financial impact and operating losses due to insider intrusions are increasing. But these studies often disagree on what constitutes an “insider;” indeed, many define it only implicitly. In theory, appropriate selection of, and enforcement of, properly specified security policies should prevent legitimate users from abusing(More)
The combination of multiple classifiers using ensemble methods is increasingly important for making progress in a variety of difficult prediction problems. We present a comparative analysis of several ensemble methods through two case studies in genomics, namely the prediction of genetic interactions and protein functions, to demonstrate their efficacy on(More)
Much of the literature on insider threat assumes, explicitly or implicitly, a binary, perimeter-based notion of an insider. However, it is generally accepted that this notion is unrealistic. The Attribute-Based Group Access Control (ABGAC) framework is a generalization of Role-Based Access Control (RBAC) which allows us to define a non-binary notion of(More)