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Strict control over the scheduling and execution of processor resources is essential for many fixed-priority real-time applications. To facilitate this common requirement, the Real-Time CORBA (RT-CORBA) specification defines standard middleware features that support end-to-end predictability for operations in such applications. One of the most important(More)
To be an effective platform for performance-sensitive real-time systems, commercial-off-the-shelf (COTS) distributed object computing (DOC) middleware must support application quality of service (QoS) requirements end-to-end. However, conventional DOC middleware does not provide this support, which makes it unsuited for applications with stringent la-tency,(More)
The fast Gauss transform allows for the calculation of the sum of N Gaussians at M points in O(N + M) time. Here, we extend the algorithm to a wider class of kernels, motivated by quadrature issues that arise in using integral equation methods for solving the heat equation on moving domains. In particular, robust high-order product integration methods(More)
Shotgun proteomics coupled with database search software allows the identification of a large number of peptides in a single experiment. However, some existing search algorithms, such as SEQUEST, use score functions that are designed primarily to identify the best peptide for a given spectrum. Consequently, when comparing identifications across spectra, the(More)
To be an effective platform for performance-sensitive real-time systems, commodity-off-the-shelf (COTS) distributed object computing (DOC) middleware must support application quality of service (QoS) requirements end-to-end. However, conventional COTS DOC middleware does not provide this support, which makes it unsuited for applications with stringent(More)
The goal of many shotgun proteomics experiments is to determine the protein complement of a complex biological mixture. For many mixtures, most methodological approaches fall significantly short of this goal. Existing solutions to this problem typically subdivide the task into two stages: first identifying a collection of peptides with a low false discovery(More)
We have developed a mathematical approach to the study of dynamical biological networks, based on combining large-scale numerical simulation with nonlinear "dimensionality reduction" methods. Our work was motivated by an interest in the complex organization of the signaling cascade centered on the neuronal phosphoprotein DARPP-32 (dopamine- and(More)
Various biological processes exhibit characteristics that vary dramatically in response to different input conditions or changes in the history of the process itself. One of the examples studied here, the Ras-PKC-mitogen-activated protein kinase (MAPK) bistable pathway, follows two distinct dynamics (modes) depending on duration and strength of EGF(More)
We describe and evaluate two algorithms for Neyman-Pearson (NP) classification problem which has been recently shown to be of a particular importance for bipartite ranking problems. NP classification is a nonconvex problem involving a constraint on false negatives rate. We investigated batch algorithm based on DC programming and stochastic gradient method(More)
We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i)(More)