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Inconsistencies in the preparation of histology slides make it difficult to perform quantitative analysis on their results. In this paper we provide two mechanisms for overcoming many of the known inconsistencies in the staining process, thereby bringing slides that were processed or stored under very different conditions into a common, normalized space to(More)
Comparative Effectiveness Research (CER) is designed to provide research evidence on the effectiveness and risks of different therapeutic options on the basis of data compiled from subpopulations of patients with similar medical conditions. Electronic Health Record (EHR) system contain large volumes of patient data that could be used for CER, but the data(More)
Twenty-first century life sciences have transformed into data-enabled (also called data-intensive, data-driven, or big data) sciences. They principally depend on data-, computation-, and instrumentation-intensive approaches to seek comprehensive understanding of complex biological processes and systems (e.g., ecosystems, complex diseases , environmental,(More)
How can a visual system or cognitive system use the changing relationships between moving visual elements to decide which elements belong together as groups (or objects)? We have constructed a neural circuit model that selects object groupings based on global Gestalt common-fate evidence and uses information about the behavior of each group to predict the(More)
The present study used inbred, histocompatible Fischer 344 (FIS) and Lewis (LEW) rats to begin to explore the role of the hypothalamic-pituitary-adrenal (HPA) axis in the immune processes and pain behavior associated with the carrageenan model of acute hindpaw inflammation. Because the HPA axis contributes in part to morphine's analgesic and(More)
The success of research in the field of maternal-infant health, or in any scientific field, relies on the adoption of best practices for data and knowledge management. Prior work by our group and others has identified evidence-based solutions to many of the data management challenges that exist, including cost-effective practices for ensuring high-quality(More)
Genomics research presents technical, computational, and analytical challenges that are well recognized. Less recognized are the complex sociological, psychological, cultural, and political challenges that arise when genomics research takes place within a large, decentralized academic institution. In this paper, we describe a Service-Oriented Architecture(More)
—Genomic research involves a considerable amount of intensive computational and data management challenges including varying demand for computing resources, large data staging, management of complex workflows, and managing data and metadata across thousands of experiments and datasets. To address these challenges, researchers are typically forced to acquire(More)