Aplicação dos lipossomas como estratégia para superar a resistência bacteriana aos antibióticos

Dissertação de mestrado, Ciências Farmacêuticas, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

Genetic and bacterial programming for B-Spline neural networks design

The design phase of B-spline neural networks is a highly computationally complex task. Existent heuristics have been found to be highly dependent on the initial conditions employed. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this paper, the Bacterial Programming approach is presented, which is based on the replication of the microbial evolution phenomenon. This technique produces an efficient topology search, obtaining additionally more consistent solutions.

Design of B-spline neural networks using a bacterial programming approach

The design phase of B-spline neural networks represents a very high computational task. For this purpose, heuristics have been developed, but have been shown to be dependent on the initial conditions employed. In this paper a new technique, Bacterial Programming, is proposed, whose principles are based on the replication of the microbial evolution phenomenon. The performance of this approach is illustrated and compared with existing alternatives.

Uma abordagem de matabolómica no estudo comparativo do metabolismo de glucose e galactose no patogénico humano Streptococcus pneumoniae

Dissertação mest., Ciências Biomédicas, Universidade do Algarve, 2010

A biotecnologia no ensino das ciências do 3º ciclo: desenvolvimento de experiências didácticas utilizando a acção de biocatalisadores imobilizados

Dissertação mest., Biologia e Geologia, Universidade do Algarve, 2007

Variabilidade genómica de Citrus tristeza virus e transformação genética de Citrus aurantium L. com vista à obtenção de resistência

Tese de dout., Biologia, Faculdade de Engenharia de Recursos Naturais, Univ. do Algarve, 2003

Produção e purificação da proteína rica em gla (grp) humana recombinante

Dissertação de mest., Biologia Molecular e Microbiana, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2011

Tóxicos veiculados por alimentos - diapositivos de apoio às aulas

Caracterização dos acidentes de intoxicação alimentar provocados por constituintes naturais dos alimentos e por ingestão de alimentos contaminados: - Toxinas de origem natural: produzidas por vegetais; produzidas por cogumelos; micotoxinas; substâncias tóxicas produzidas por animais; ficotoxinas; aminas biogénicas; toxinas de origem bacteriana;bactérias, vírus e parasitas patogénicos veiculados por alimentos. - Metais pesados. - Fitofármacos e medicamentos de uso veterinário; - Substâncias que resultam de processos de fabrico, conservação ou preparação dos alimentos.

Study of influence of regulatory polymorphisms of expression in development of breast cancer

The human genome has millions of genetics variants that can affect gene expression. These variants are known as cis-regulatory variants and are responsible for intra-species phenotypic differences and individual susceptibility to disease. One of the diseases affected by cis-regulatory variants is breast cancer. Breast cancer is one of the most common cancers, with approximately 4500 new cases each year in Portugal. Breast cancer has many genes mutated and TP53 has been shown to be relevant for this disease. TP53 is one of the most commonly mutated genes in human cancer and it is involved in cell cycle regulation and apoptosis. Previous work by Maia et al has shown that TP53 has differential allelic expression (DAE), which suggests that this gene may be under the influence of cis-regulatory variants. Also, its DAE pattern is totally altered in breast tumours with normal copy number. We hypothesized that cis-regulatory variants affecting TP53 may have a role in breast cancer development and treatment. The present work aims to identify the cis-regulatory variants playing a role in TP53 expression, using in silico, in vitro and in vivo approaches. By bioinformatic tools we have identified candidate cis-regulatory variants and predicted the possible transcription factor binding sites that they affect. By EMSA we studied DNA-protein interactions in this region of TP53. The in silico analysis allowed us to identified three candidate cis-regulatory SNPs which may affect the binding of seven transcription factors. However, the EMSA experiments have not been conclusive and we have not yet confirmed whether any of the identified SNPs are associated with gene expression control of TP53. We will carry out further experiments to validate our findings.

Design of neuro-fuzzy models by evolutionary and gradient-based algorithms

All systems found in nature exhibit, with different degrees, a nonlinear behavior. To emulate this behavior, classical systems identification techniques use, typically, linear models, for mathematical simplicity. Models inspired by biological principles (artificial neural networks) and linguistically motivated (fuzzy systems), due to their universal approximation property, are becoming alternatives to classical mathematical models. In systems identification, the design of this type of models is an iterative process, requiring, among other steps, the need to identify the model structure, as well as the estimation of the model parameters. This thesis addresses the applicability of gradient-basis algorithms for the parameter estimation phase, and the use of evolutionary algorithms for model structure selection, for the design of neuro-fuzzy systems, i.e., models that offer the transparency property found in fuzzy systems, but use, for their design, algorithms introduced in the context of neural networks. A new methodology, based on the minimization of the integral of the error, and exploiting the parameter separability property typically found in neuro-fuzzy systems, is proposed for parameter estimation. A recent evolutionary technique (bacterial algorithms), based on the natural phenomenon of microbial evolution, is combined with genetic programming, and the resulting algorithm, bacterial programming, advocated for structure determination. Different versions of this evolutionary technique are combined with gradient-based algorithms, solving problems found in fuzzy and neuro-fuzzy design, namely incorporation of a-priori knowledge, gradient algorithms initialization and model complexity reduction.

Bacteriobenthos diversity in the surface of different sediment environments in Ria Farmosa

Dissertação de Mestrado, Biologia Marinha, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

Locust bean gum-based microparticles for pulmonary delivery of antibiotics

Dissertação de Mestrado, Ciências Biomédicas, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2016