Brown University Center for Statistical Sciences Seminar
Centers for Disease Control and Prevention | |
Abstract: A variety of statistical methods exist for detecting haplotype-disease association using genetic data from a case-control study. As such data often consist of unphased genotypes (resulting in haplotype ambiguity), such statistical methods typically apply the Expectation-Maximization (EM) algorithm for inference. However, the majority of these methods fail to perform inference on the effect of particular haplotypes or haplotype features on disease risk. As such inference is valuable, a retrospective likelihood is developed for estimating and testing the effects of specific features of SNP-based haplotypes on disease risk assuming unphased genotype data from a case-control study. The proposed method has a flexible structure that allows, among other choices, modeling of multiplicative, dominant, and recessive effects of specific haplotype features on disease risk. In addition, the method relaxes the requirement of Hardy-Weinberg Equilibrium (HWE) of haplotype frequencies in case subjects, which is typically required at EM-based haplotype methods. Also, the method easily accommodates missing SNP information. Finally, the method allows for asymptotic, permutation-based or bootstrap inference. The new method is applied to case-control SNP genotype data from the Finland-United States Investigation of Non-Insulin-Dependent Diabetes Mellitus (FUSION) Genetics study and identify two haplotypes that appear to be significantly associated with type 2 diabetes.
**Sponsored by the C.V. Starr Foundation Lectureship Fund
***Co Sponsored by The Center for Genetics and Genomics
Brown Applied Mathematics Pattern Theory and Vision Seminar
Abstract: In neuroscience, it is often necessary to detect neural activity that exhibits certain temporal pattern. This problem can be formulated as detection of patterned clusters of points ("targets"). I will describe an approach to this problem which also applies to detection for continuous-valued signals. Detection is considered classification based on likelihood ratio. Under certain Poisson assumptions on the point processes, the classification is equivalent to linear filtering. I will present results using this approach in neuroscience, such as replayed pattern in spontaneous sleep neuronal activity of the birdsong system. Large deviations involved in this approach will also be discussed.
Center for Fluid Mechanics Seminar
Department of Chemical Engineering | |
Abstract: Stability to coalescence of two drops pressed together by an external force or flow is controlled by the drainage of a thin liquid film that separates drop interfaces. Our recent results indicate that for deformable drops with surfactant-free interfaces, the external flow can qualitatively affect film drainage dynamics. In some cases the flow can prevent drop coalescence, and in others it induces exponential drainage of the film. These results are in contrast with previous analyses that assumed that under low-capillary-number conditions an external flow merely provides the pushing force. We also show that generally accepted assumptions regarding long-time dynamics of drops pressed together in the absence of an external flow are not valid, and we derive a correct asymptotic behavior.
Brown Analysis Seminar
Applied Mathematics Colloquium
Abstract: By the end of the 18th century, three main traditions in mechanics were evident: the approach based upon Newton's three laws, and stressing central forces; efforts to establish energy conservation, and its interchange with work; and an algebraic style, using principles such as least action and virtual work.
A programme of mathematicised molecularism was proposed around 1804 by Laplace, which flourished for about a decade and produced important results in several areas of physics, especially heat theory and physical optics.
Scientific Computing Seminar
Abstract: Sustained hypersonic flight, as an end in itself for rapid transport, or as an integral element of safe, routine and affordable access to space, has seen renewed emphasis because of its potential to revolutionize commercial and military activities. The environment encountered in proposed flight envelopes cannot be overcome by current technology because of the extreme thermal loads and drag encountered, which is aggravated by a sharp reduction in efficiency of existing propulsion systems at high-speeds. This deficiency in present technology has provided fresh impetus to exploration of revolutionary techniques for flow control and manipulation. Among the most promising are those that leverage electromagnetic force and energy interactions to exploit the natural or artifically enhanced electrically conducting nature of high-speed flows. In this talk, we describe recent sustained efforts at developing high-resolution methods for magnetogasdynamics(MGD), addressing particularly the peculiarities of the anticipated aerospace environment. Verification and validation efforts will be summarized and followed by analysis of several 2-D and 3-D flow control applications. These include Type IV shock-on-cowl lip load mitigation, an eddy-current based momentum transfer approach to inhibit 3-D separation and a complete scramjet flow-through simulation with MGD energy bypass.
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