DETERMINING THE GENOTYPE-PHENOTYPE CONNECTION IN SYNTHETIC INDUCIBLE GENE EXPRESSION SYSTEMS

Introduction Gene expression is an important process whereby the genotype controls an individual cell’s phenotype. However, even genetically identical cells display a variety of phenotypes, which may be attributed to differences in their environment. Yet, even after controlling for these two factors, individual phenotypes still diverge due to noisy gene expression. Synthetic gene expression systems allow investigators to isolate, control, and measure the effects of noise on cell phenotypes. I used mathematical and computational methods to design, study, and predict the behavior of synthetic gene expression systems in S. cerevisiae, which were affected by noise. Methods I created probabilistic biochemical reaction models from known behaviors of the tetR and rtTA genes, gene products, and their gene architectures. I then simplified these models to account for essential behaviors of gene expression systems. Finally, I used these models to predict behaviors of modified gene expression systems, which were experimentally verified. Results Cell growth, which is often ignored when formulating chemical kinetics models, was essential for understanding gene expression behavior. Models incorporating growth effects were used to explain unexpected reductions in gene expression noise, design a set of gene expression systems with “linear” dose-responses, and quantify the speed with which cells explored their fitness landscapes due to noisy gene expression. Conclusions Models incorporating noisy gene expression and cell division were necessary to design, understand, and predict the behaviors of synthetic gene expression systems. The methods and models developed here will allow investigators to more efficiently design new gene expression systems, and infer gene expression properties of TetR based systems.

Design and implementation of a multicriteria medical decision support system for diagnosis and treatment

Health care providers face the problem of trying to make decisions with inadequate information and also with an overload of (often contradictory) information. Physicians often choose treatment long before they know which disease is present. Indeed, uncertainty is intrinsic to the practice of medicine. Decision analysis can help physicians structure and work through a medical decision problem, and can provide reassurance that decisions are rational and consistent with the beliefs and preferences of other physicians and patients. ^ The primary purpose of this research project is to develop the theory, methods, techniques and tools necessary for designing and implementing a system to support solving medical decision problems. A case study involving “abdominal pain” serves as a prototype for implementing the system. The research, however, focuses on a generic class of problems and aims at covering theoretical as well as practical aspects of the system developed. ^ The main contributions of this research are: (1) bridging the gap between the statistical approach and the knowledge-based (expert) approach to medical decision making; (2) linking a collection of methods, techniques and tools together to allow for the design of a medical decision support system, based on a framework that involves the Analytic Network Process (ANP), the generalization of the Analytic Hierarchy Process (AHP) to dependence and feedback, for problems involving diagnosis and treatment; (3) enhancing the representation and manipulation of uncertainty in the ANP framework by incorporating group consensus weights; and (4) developing a computer program to assist in the implementation of the system. ^

Safer sex choices among African-American college women

The purpose of this dissertation was to explore and describe the factors that influence the safer sex choices of African-American college women. The pandemic of HIV and the prevalence of other sexually transmitted diseases has disproportionately affected African-American females. As young women enter college they are faced with a myriad of choices. Unprotected sexual exploration is one choice that can lead to deadly consequences. This dissertation explores, through in-depth interviews, the factors associated with the decision to practice or not practice safe sex. ^ The first study describes the factors associated with increased sexual risk taking among African-American college women. Sexual risk taking or sex without a condom was found to be more likely when issues of self or partner pleasure were raised. Participants were also likely to have sexual intercourse without a condom if they desired a long term relationship with their partner. ^ The second study examined safe sex decision making processes among a group of African-American college women. Women were found to employ both emotional and philosophical strategies to determine their safe sex behavior. These strategies range from assessing a partner's physical capabilities and appearance to length of the dating relationship. ^ The third study explores the association between knowledge and risk perception as predictors for safer sex behaviors. Knowledge of HIV/AIDS and other STDs was not found to be a determinant of safer sex behavior. Perception of personal risk was also not highly correlated with consistent safer sex behavior. ^ These studies demonstrate the need for risk-based safer sex education and intervention programs. The current climate of knowledge-based program development insures that women will continue to predicate their decision to practice safer sex on their limited perception and understanding of the risks associated with unprotected sexual behavior. Further study into the emotional and philosophical determinants of sexual behavior is necessary for the realistic design of applicable and meaningful interventions. ^