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In this talk I will present our recent work on prediction and modeling of high-dimensional systems in living tissue, with application to biomarker discovery and the inference of Boolean regulatory networks. The first part of the talk will discuss biomarker discovery via Pattern Recognition and Bayesian Signal Processing methods applied to small-sample, high-dimensional data from gene-expression microarrays and protein-abundance Mass Spectrometry (LC-MS). The second half will deal with small-sample inference issues of discrete-time Boolean regulatory circuits. These involve models of highly-nonlinear dynamical systems that govern the evolution of cellular states, but which may be applied as well to climate, ocean dynamics and weather prediction. Host: Frank Alexander, fja@lanl.gov, 665-4518. Information Science and Technology Center (ISTC) |