18 resultados para Biological networks


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.

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The bronze bug is an invasive Australian pest that has reached eucalypt production areas worldwide in <10 years. The fi rst record in South America was in 2005 in Argentina. Collaboration in the region towards a unifi ed strategy for the management of the bronze bug started soon after the dispersal of the pest into Brazil and Uruguay was confi rmed. Here, we present the main achievements of this collaboration in four main topics: 1) biology of the pest, 2) monitoring, 3) biological control, and 4) cooperative networks. Two mass rearing procedures have been implemented in the region with relative success, allowing basic biological studies on the pest. Continuous monitoring in the region for >5 years has provided a reasonable knowledge on seasonal patterns of T. peregrinus. Biological control strategies developed include the use of local natural enemies of T. peregrinus, the development of biopesticides, and the introduction of Cleruchoides noackae, an egg parasitoid of T. peregrinus from Australia. We review the main achievements in each country. Finally, a regional network of institutions, researchers, and students has strengthened in the region, providing a solid background for future collaboration.