Variation in body size and sexual dimorphism across geographical and environmental space in the frogs Limnodynastes tasmaniensis and L. peronii

This study aimed to identify potential factors responsible for geographically structured morphological variation within the widespread Australian frogs Limnodynastes tasmaniensis Gunther and L. peronii Dumeril & Bibron. There was support for James's rule, and both latitude and present climate explained large amounts of the variation in body size and shape (particularly in L. peronii). There was also some support for the influence of several biogeographical barriers. Finally, both species were sexually dimorphic for body size and the degree of sexual size dimorphism (SSD) varied geographically. Climate was an important explanation for SSD variation in L. peronii, while latitude was most important for L. tasmaniensis. Geographical variations in sexual selection via male-male physical competition and climate-related resources are suggested as potential explanations for SSD variation in L. peronii. (C) 2004 The Linnean Society of London.

Focusing in on structural genomics: The University of Queensland structural biology pipeline

The flood of new genomic sequence information together with technological innovations in protein structure determination have led to worldwide structural genomics (SG) initiatives. The goals of SG initiatives are to accelerate the process of protein structure determination, to fill in protein fold space and to provide information about the function of uncharacterized proteins. In the long-term, these outcomes are likely to impact on medical biotechnology and drug discovery, leading to a better understanding of disease as well as the development of new therapeutics. Here we describe the high throughput pipeline established at the University of Queensland in Australia. In this focused pipeline, the targets for structure determination are proteins that are expressed in mouse macrophage cells and that are inferred to have a role in innate immunity. The aim is to characterize the molecular structure and the biochemical and cellular function of these targets by using a parallel processing pipeline. The pipeline is designed to work with tens to hundreds of target gene products and comprises target selection, cloning, expression, purification, crystallization and structure determination. The structures from this pipeline will provide insights into the function of previously uncharacterized macrophage proteins and could lead to the validation of new drug targets for chronic obstructive pulmonary disease and arthritis. (c) 2006 Elsevier B.V. All rights reserved.

Tracking the states of a nonlinear system in the weight-space of a feed-forward neural network

Nonlinear, non-stationary signals are commonly found in a variety of disciplines such as biology, medicine, geology and financial modeling. The complexity (e.g. nonlinearity and non-stationarity) of such signals and their low signal to noise ratios often make it a challenging task to use them in critical applications. In this paper we propose a new neural network based technique to address those problems. We show that a feed forward, multi-layered neural network can conveniently capture the states of a nonlinear system in its connection weight-space, after a process of supervised training. The performance of the proposed method is investigated via computer simulations.