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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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In this seminar, I will present two novel statistical techniques, one for analysis of multiple curves and one for analysis of multiple peaks.
Analysis of multiple curves was motivated by a genetic microarray
experiment. The data consist of a large number of short expression
profiles over time, which are to be grouped based on their shapes.
This problem is challenging because a large number of profiles are observed over a small number of time points and because the
contrast-to-noise ratio for observations tends to be low. In addition, a fair number of profiles can be constant. To address this and similar problems, a new statistical clustering method based on transformation and smoothing is introduced.
Analysis of multiple peaks was developed in the context of NMR-based protein structure determination. An NMR experiment produces signal data at a large number of time points, which can be investigated in the frequency domain. The primary objective is to identify the frequency peaks, and to estimate their location, width, and height. The challenges in this application are that the signal is inhomogeneous, and some of the peaks are partially or totally overlapping. A new statistical approach based on a finite mixture model of nonlinear regressions is presented.
