Showing papers by "Robert F. Stengel published in 2006"

Relationship of gene expression and chromosomal abnormalities in colorectal cancer.

Abstract: Several studies have verified the existence of multiple chromosomal abnormalities in colon cancer. However, the relationships between DNA copy number and gene expression have not been adequately explored nor globally monitored during the progression of the disease. In this work, three types of array-generated data (expression, single nucleotide polymorphism, and comparative genomic hybridization) were collected from a large set of colon cancer patients at various stages of the disease. Probes were annotated to specific chromosomal locations and coordinated alterations in DNA copy number and transcription levels were revealed at specific positions. We show that across many large regions of the genome, changes in expression level are correlated with alterations in DNA content. Often, large chromosomal segments, containing multiple genes, are transcriptionally affected in a coordinated way, and we show that the underlying mechanism is a corresponding change in DNA content. This implies that whereas specific chromosomal abnormalities may arise stochastically, the associated changes in expression of some or all of the affected genes are responsible for selecting cells bearing these abnormalities for clonal expansion. Indeed, particular chromosomal regions are frequently gained and overexpressed (e.g., 7p, 8q, 13q, and 20q) or lost and underexpressed (e.g., 1p, 4, 5q, 8p, 14q, 15q, and 18) in primary colon tumors, making it likely that these changes favor tumorigenicity. Furthermore, we show that these aberrations are absent in normal colon mucosa, appear in benign adenomas (albeit only in a small fraction of the samples), become more frequent as disease advances, and are found in the majority of metastatic samples.

Probabilistic Control of Nonlinear Uncertain Systems

Abstract: Robust controllers for nonlinear systems with uncertain parameters can be reliably designed using probabilistic methods. In this chapter, a design approach based on the combination of stochastic robustness and dynamic inversion is presented for general systems that have a feedback-linearizable nominal system. The efficacy of this control approach is illustrated through the design of flight control systems for a hypersonic aircraft and a highly nonlinear, complex aircraft model. The proposed stochastic robust nonlinear control explores the direct design of nonlinear flight control logic; therefore the final design accounts for all significant nonlinearities in the aircraft’s high-fidelity simulation model. Monte Carlo simulation is used to estimate the likelihood of closed-loop system instability and violation of performance requirements subject to variations of the probabilistic system parameters. The stochastic robustness cost function is defined in terms of the probabilities that design criteria will not be satisfied. We use randomized algorithms, in particular genetic algorithms, to search the design parameters of the parameterized controller with feedback linearization structure. The design approach is an extension of earlier methods for probabilistic robust control of linear systems. Prior results are reviewed, and the nonlinear approach is presented.