Evolutionary synthesis of stochastic gene network models using feature-based search spaces

A feature-based fitness function is applied in a genetic programming system to synthesize stochastic gene regulatory network models whose behaviour is defined by a time course of protein expression levels. Typically, when targeting time series data, the fitness function is based on a sum-of-errors involving the values of the fluctuating signal. While this approach is successful in many instances, its performance can deteriorate in the presence of noise. This thesis explores a fitness measure determined from a set of statistical features characterizing the time series' sequence of values, rather than the actual values themselves. Through a series of experiments involving symbolic regression with added noise and gene regulatory network models based on the stochastic 'if-calculus, it is shown to successfully target oscillating and non-oscillating signals. This practical and versatile fitness function offers an alternate approach, worthy of consideration for use in algorithms that evaluate noisy or stochastic behaviour.

The Effectiveness of Learning Portfolios: A Study of Quality Assurance Programs of Selected Health Regulatory Colleges in Ontario

Health regulatory colleges promote quality practice and continued competence through Quality Assurance (QA) programs. For many colleges, a QA program includes the use of portfolios that incorporate self-directed learning. The purpose of this study was to determine some of the issues surrounding the effectiveness of QA portfolio programs. The literature review revealed that portfolios are valuable tools, but gaps in knowledge include a comparative analysis of QA programs and the perspective of regulatory college administrators. Data were collected through interviews with 6 administrators and a review of 14 portfolio models described on college websites. The results from the two data sources were applied to Robert Stake's responsive evaluation framework to identify issues related to the portfolio's effectiveness (Stake, 1967). The learning components of portfolios were analyzed through the humanist and constructivist lenses. All 14 portfolio models were found to have 3 main components: self-diagnosis, learning plan and activities, and self-evaluation. However, differences were uncovered in learners' autonomy in selecting learning activities, methods of portfolio evaluation, and the relationship between the portfolio and other QA components. The results revealed a dual philosophy of learning in portfolio models and an apparent contradiction between the needs of the individual learner and the organization. Paths for future research include the tenuous relationship between competence and learning, and the impact of technical approaches on selfdirected learning initiatives. A key recommendation is to acknowledge the unique identity of each profession so that health regulatory colleges can address legislative demands and learner needs.