5 resultados para System Development

em Repositório da Produção Científica e Intelectual da Unicamp


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One of the great challenges of the scientific community on theories of genetic information, genetic communication and genetic coding is to determine a mathematical structure related to DNA sequences. In this paper we propose a model of an intra-cellular transmission system of genetic information similar to a model of a power and bandwidth efficient digital communication system in order to identify a mathematical structure in DNA sequences where such sequences are biologically relevant. The model of a transmission system of genetic information is concerned with the identification, reproduction and mathematical classification of the nucleotide sequence of single stranded DNA by the genetic encoder. Hence, a genetic encoder is devised where labelings and cyclic codes are established. The establishment of the algebraic structure of the corresponding codes alphabets, mappings, labelings, primitive polynomials (p(x)) and code generator polynomials (g(x)) are quite important in characterizing error-correcting codes subclasses of G-linear codes. These latter codes are useful for the identification, reproduction and mathematical classification of DNA sequences. The characterization of this model may contribute to the development of a methodology that can be applied in mutational analysis and polymorphisms, production of new drugs and genetic improvement, among other things, resulting in the reduction of time and laboratory costs.

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Biofilm formation on reverse osmosis (RO) systems represents a drawback in the application of this technology by different industries, including oil refineries. In RO systems the feed water maybe a source of microbial contamination and thus contributes for the formation of biofilm and consequent biofouling. In this study the planktonic culturable bacterial community was characterized from a feed water of a RO system and their capacities were evaluated to form biofilm in vitro. Bacterial motility and biofilm control were also analysed using phages. As results, diverse Protobacteria, Actinobacteria and Bacteroidetes were identified. Alphaproteobacteria was the predominant group and Brevundimonas, Pseudomonas and Mycobacterium the most abundant genera. Among the 30 isolates, 11 showed at least one type of motility and 11 were classified as good biofilm formers. Additionally, the influence of non-specific bacteriophage in the bacterial biofilms formed in vitro was investigated by action of phages enzymes or phage infection. The vB_AspP-UFV1 (Podoviridae) interfered in biofilm formation of most tested bacteria and may represent a good alternative in biofilm control. These findings provide important information about the bacterial community from the feed water of a RO system that may be used for the development of strategies for biofilm prevention and control in such systems.

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• Microsatellite primers were developed for the tree species Genipa americana (Rubiaceae) for further population genetic studies. • We identified 144 clones containing 65 repeat motifs from a genomic library enriched for (CT)8 and (GT)8 motifs. Primer pairs were developed for 32 microsatellite loci and validated in 40 individuals of two natural G. americana populations. Seventeen loci were polymorphic, revealing from three to seven alleles per locus. The observed and expected heterozygosities ranged from 0.24 to 1.00 and from 0.22 to 0.78, respectively. • The 17 primers identified as polymorphic loci are suitable to study the genetic diversity and structure, mating system, and gene flow in G. americana.

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There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist 'Eve' designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax.

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Universidade Estadual de Campinas . Faculdade de Educação Física