Handel opera presentation, past and present : a thesis presented in partial fulfilment of the requirements for the degree of Master of Music at Massey University, Wellington, New Zealand

What differences, if any, exist between the performance of Handel opera during his lifetime, and contemporary performances? To what extent do these differences reflect the need to adapt Handel's operas when performed out of their original context, and how does knowledge of original performance practices enhance the singer's ability to interpret and present characters in performance? This study investigates the ideas outlined above, exploring the social and cultural environment of opera seria, its conventions, and the way in which Handel's operas were presented during his lifetime, later providing a comparison with contemporary productions. It aims to enhance understanding of the production and musical aspects of staging a Handel opera, and to illustrate how this knowledge can assist in performance

Using Reaction Times and Binary Responses to Estimate Psychophysical Performance: An Information-Theoretic Analysis

As the strength of a stimulus increases, the proportions of correct binary responses increases, which define the psychometric function. Simultaneously, mean reaction times (RT) decrease, which collectively define the chronometric function. However, RTs are traditionally ignored when estimating psychophysical parameters, even though they may provide additional Shannon information. Here, we extend Palmer et al's (2005) proportional-rate diffusion model (PRD) by: (a) fitting individual RTs to an inverse Gaussian distribution, (b) including lapse rate, (c) point-of-subjective-equality (PSE) parameters, and, (d) using a two-alternative forced choice (2AFC) design based on the proportion of times a variable comparison stimulus is chosen. Maximum likelihood estimates of mean RT values (from fitted inverse Gaussians) and binary responses were fitted both separately and in combination to this extended PRD (EPRD) model, to obtain psychophysical parameter values. Values estimated from binary responses alone (i.e., the psychometric function) were found to be similar to those estimated from RTs alone (i.e., the chronometric function), which provides support for the underlying diffusion model. The EPRD model was then used to estimate the mutual information between binary responses and stimulus strength, and between RTs and stimulus strength. These provide conservative bounds for the average amount of Shannon information the observer gains about stimulus strength on each trial. For the human experiment reported here, the observer gains between 2.68 and 3.55 bits/trial. These bounds are monotonically related to a new measure, the Shannon increment, which is the expected value of the smallest change in stimulus strength detectable by an observer

GeneWeaver: a web-based system for integrative functional genomics

High-throughput genome technologies have produced a wealth of data on the association of genes and gene products to biological functions. Investigators have discovered value in combining their experimental results with published genome-wide association studies, quantitative trait locus, microarray, RNA-sequencing and mutant phenotyping studies to identify gene-function associations across diverse experiments, species, conditions, behaviors or biological processes. These experimental results are typically derived from disparate data repositories, publication supplements or reconstructions from primary data stores. This leaves bench biologists with the complex and unscalable task of integrating data by identifying and gathering relevant studies, reanalyzing primary data, unifying gene identifiers and applying ad hoc computational analysis to the integrated set. The freely available GeneWeaver (http://www.GeneWeaver.org) powered by the Ontological Discovery Environment is a curated repository of genomic experimental results with an accompanying tool set for dynamic integration of these data sets, enabling users to interactively address questions about sets of biological functions and their relations to sets of genes. Thus, large numbers of independently published genomic results can be organized into new conceptual frameworks driven by the underlying, inferred biological relationships rather than a pre-existing semantic framework. An empirical ‘ontology’ is discovered from the aggregate of experimental knowledge around user-defined areas of biological inquiry

Integrating Computational Biology and Forward Genetics in Drosophila

Genetic screens are powerful methods for the discovery of gene–phenotype associations. However, a systems biology approach to genetics must leverage the massive amount of “omics” data to enhance the power and speed of functional gene discovery in vivo. Thus far, few computational methods for gene function prediction have been rigorously tested for their performance on a genome-wide scale in vivo. In this work, we demonstrate that integrating genome-wide computational gene prioritization with large-scale genetic screening is a powerful tool for functional gene discovery. To discover genes involved in neural development in Drosophila, we extend our strategy for the prioritization of human candidate disease genes to functional prioritization in Drosophila. We then integrate this prioritization strategy with a large-scale genetic screen for interactors of the proneural transcription factor Atonal using genomic deficiencies and mutant and RNAi collections. Using the prioritized genes validated in our genetic screen, we describe a novel genetic interaction network for Atonal. Lastly, we prioritize the whole Drosophila genome and identify candidate gene associations for ten receptor-signaling pathways. This novel database of prioritized pathway candidates, as well as a web application for functional prioritization in Drosophila, called Endeavour-HighFly, and the Atonal network, are publicly available resources. A systems genetics approach that combines the power of computational predictions with in vivo genetic screens strongly enhances the process of gene function and gene–gene association discovery

Considerations from the IQ Induction Working Group in Response to Drug-Drug Interaction Guidances from Regulatory Agencies: Focus on CYP3A4 mRNA in vitro response thresholds, variability, and clinical relevance

Here the IQ induction working group presents an assessment of best practice for data interpretation of in vitro induction, specifically, response thresholds, variability, application of controls and translation to clinical risk assessment with focus on CYP3A4 mRNA. Single concentration control data and Emax/EC50 data for prototypical CYP3A4 inducers were compiled from many human hepatocyte donors, repeated over time, in different laboratories. Clinical CYP3A induction and in vitro data were gathered for 51 compounds, 16 of which were proprietary from IQ member companies. A large degree of variability was observed in both the clinical and in vitro induction responses gathered, yet analysis confirmed in vitro data are able to predict clinical induction risk. Following extensive examination of this large dataset, the following recommendations are proposed: • CYP induction should continue to be evaluated in three separate human donors in vitro. • In light of empirically divergent responses in rifampicin control and most test inducers, normalization of data to percent positive control appears to be of limited benefit. • Two-fold induction, with concentration dependence, is an acceptable threshold for positive identification of in vitro CYP3A4 mRNA induction. • To reduce the risk of false positives, in the absence of a concentration dependent response, induction ≥ 2-fold should be observed in more than one donor to classify a compound as an in vitro inducer. • If qualifying a compound as negative for CYP3A4 mRNA induction, the magnitude of maximal rifampicin response in that donor should be ≥10-fold. • Inclusion of a negative control adds no value beyond that of the vehicle control