Brown Applied Mathematics Pattern Theory and Vision Seminar
Brown Analysis Seminar
Lefschetz Center for Dynamical Systems Seminar
Boston University/Brown University PDE Seminar
Lefschetz Center for Dynamical Systems Seminar
Boston University/Brown University PDE Seminar
Center for Computational Molecular Biology Seminar Series
Abstract: Computer systems specification, analysis and diagnosis are arguably one of the most practically important and essential topics in computer science and engineering. This research resulted in tools and environments that allow engineers to specify and analyze hardware and networks as well as recognize and correct unexpected behaviors, network intrusion or anomalies. Medicine and biology, on surface present similar problems. Our cells are provided with basic instructions that when executed properly enable living organisms to function properly. As a result of genetic, epigenetic or environmental perturbations our cells exhibit aberrations in their functional behaviors leading to major diseases such as cancer or diabetes, causing inordinate suffering for patients and their families. We focus on insulin signaling and related processes such as inflammation and glucose metabolism. We describe our on-going projects aimed towards identification of the full dictionary of parts and their cellular interactions that are involved in these important biological functions using both network and evolutionary approaches. This work leads to better genomic annotation of newly sequenced genes and a number of novel predictions. Manipulations of several genes in these pathways have been shown to extend life in model organisms or have predicted associations with diabetes in the human population. Biology is very complex and it is often difficult to formalize the entire repertoire of "normal" or "abnormal" clinical phenotypes of age associated diseases such as Diabetes or Alzheimer's. We describe the new paradigm of network signatures of disease that allow us to recognize anomalies leading to disease at the molecular network level. Specifically, we introduce several concepts including Gene Network Enrichment Analysis (GNEA) and show how it enables biomedical researchers to identify and confirm disregulated molecular processes in diabetes and insulin resistance that elude recognition by standard methods. This work has the potential to lead to new diagnostic or prognostic biomarkers as well as new drug targets. This work describes joint research performed at Boston University, Harvard Medical School, Joslin Diabetes Center, Harvard School of Public Health and the National Center for Biomedical Computing (I2B2) at Harvard Partners.
Scientific Computing Seminar
Abstract: Superparameterization (SP) is a large-scale modeling system with explicit representation of small-scale processes provided by a cloud-resolving model (CRM) embedded in each column of a large-scale model. Here we present new efficient sparse space-time algorithms based on the original idea of SP: the small scale model is solved in a reduced spatially periodic domain and in addition the time interval of integration of the small scale model is reduced systematically, while keeping the same large scale dynamics. The new algorithms have been applied to a stringent two-dimensional test suite involving moist convection interacting with shear with regimes ranging from strong free and forced squall lines to dying scattered convection as the shear strength varies. The numerical results are compared with the CRM and original SP. It is shown here that for all the regimes of propagation and dying scattered convection, the large scale variables such as horizontal velocity and specific humidity are captured in a statistically accurate way based on space-time reduction of the small scale models by a factor of 1/3; thus, the new efficient algorithms for SP result in a gain of roughly a factor of 10 in efficiency while retaining a statistical accuracy on the large scale variables. These results suggest the possibility of using these efficient new algorithms for limited area mesoscale ensemble forecasting.
PDE Seminar
Abstract: We will discuss on which dimensions is the cubic fourth-order Schrodinger equation globally wellposed in the natural energy space. We will mainly concentrate on the case when the equation becomes energy-critical.
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