81 research outputs found

    Análise de repetições em dados biológicos

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    The decoding of the genomes has created new challenges on the scientific community linked to the area of computation and information technologies. Daily, new data is added to numerous databases with billions of records, coming from more advanced equipment, helping in decoding the genomes. Determine how important and relevant are these data in order to find value-added information and obviously turn them into knowledge,is the main challenge for the bioinformatics research community. The analysis of genomes and proteomes of several organisms allow us to observe the behaviour at the evolution of species. In this study, our focus goes to a particular aspect of this analysis: the repetition of some codons and their amino acids inside several orthologous genes in eukaryotic organisms. Belonging to different stages of evolution, the main objective focuses on achieving results on the evolution of these repetitions over millions of years. We now know that these repetitions in humans are the source of several neurodegenerative diseases among others. This analysis will verify the conservation or repression, of these repetitions throughout the process of speciation as well at the level of relationship that may exist between these repetitions and those diseases. For this study we have developed an algorithm for A descodificação dos genomas veio criar novos desafios na comunidade científica ligada à área da computação e da informática. Diariamente são alimentadas inúmeras bases de dados com biliões de registos provenientes de equipamentos cada vez mais evoluídos, que auxiliam na descodificação dos genomas. Determinar o quão importante e relevante são esses dados, de forma a retirar valor acrescentado – informação, e obviamente transformá-los em conhecimento, é o grande desafio actual para a comunidade de investigadores de bioinformática. A análise de genomas, bem como dos proteomas dos vários organismos permitem-nos observar o comportamento ao nível da evolução das espécies. Neste estudo focamos a atenção num aspecto particular dessa análise: as repetições de determinados codões e dos respectivos aminoácidos nos vários organismos eucariotas, especificamente em genes ortólogos. Pertencente a várias fases da evolução das espécies, o objectivo principal centra-se na obtenção de resultados quanto à evolução dessas repetições ao longo de milhões de anos. Sabemos hoje que essas repetições no ser humano são a causa de diversas doenças neuro-degenerativas, entre outras, pelo que esta análise permitirá verificar o estado de conservação ou repressão, dessas repetições ao longo do processo de especiação, bem como ao nível do relacionamento que poderá existir entre essas repetições e as doenças nos seres superiormente evoluídos. Para este estudo foi desenvolvido um algoritmo de detecção de padrões de repetição, que possibilita uma análise detalhada da localização de uma determinada sequência, bem como das sequências que melhor se ajustam ao padrão de repetição inicial.Centro de Estudos em Educação, Tecnologias e Saúd

    Análise de repetições em dados biológicos

    Get PDF
    The decoding of the genomes has created new challenges on the scientific community linked to the area of computation and information technologies. Daily, new data is added to numerous databases with billions of records, coming from more advanced equipment, helping in decoding the genomes. Determine how important and relevant are these data in order to find value-added information and obviously turn them into knowledge,is the main challenge for the bioinformatics research community. The analysis of genomes and proteomes of several organisms allow us to observe the behaviour at the evolution of species. In this study, our focus goes to a particular aspect of this analysis: the repetition of some codons and their amino acids inside several orthologous genes in eukaryotic organisms. Belonging to different stages of evolution, the main objective focuses on achieving results on the evolution of these repetitions over millions of years. We now know that these repetitions in humans are the source of several neurodegenerative diseases among others. This analysis will verify the conservation or repression, of these repetitions throughout the process of speciation as well at the level of relationship that may exist between these repetitions and those diseases. For this study we have developed an algorithm for A descodificação dos genomas veio criar novos desafios na comunidade científica ligada à área da computação e da informática. Diariamente são alimentadas inúmeras bases de dados com biliões de registos provenientes de equipamentos cada vez mais evoluídos, que auxiliam na descodificação dos genomas. Determinar o quão importante e relevante são esses dados, de forma a retirar valor acrescentado – informação, e obviamente transformá-los em conhecimento, é o grande desafio actual para a comunidade de investigadores de bioinformática. A análise de genomas, bem como dos proteomas dos vários organismos permitem-nos observar o comportamento ao nível da evolução das espécies. Neste estudo focamos a atenção num aspecto particular dessa análise: as repetições de determinados codões e dos respectivos aminoácidos nos vários organismos eucariotas, especificamente em genes ortólogos. Pertencente a várias fases da evolução das espécies, o objectivo principal centra-se na obtenção de resultados quanto à evolução dessas repetições ao longo de milhões de anos. Sabemos hoje que essas repetições no ser humano são a causa de diversas doenças neuro-degenerativas, entre outras, pelo que esta análise permitirá verificar o estado de conservação ou repressão, dessas repetições ao longo do processo de especiação, bem como ao nível do relacionamento que poderá existir entre essas repetições e as doenças nos seres superiormente evoluídos. Para este estudo foi desenvolvido um algoritmo de detecção de padrões de repetição, que possibilita uma análise detalhada da localização de uma determinada sequência, bem como das sequências que melhor se ajustam ao padrão de repetição inicial.Centro de Estudos em Educação, Tecnologias e Saúd

    GeneBrowser 2: an application to explore and identify common biological traits in a set of genes

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    <p>Abstract</p> <p>Background</p> <p>The development of high-throughput laboratory techniques created a demand for computer-assisted result analysis tools. Many of these techniques return lists of genes whose interpretation requires finding relevant biological roles for the problem at hand. The required information is typically available in public databases, and usually, this information must be manually retrieved to complement the analysis. This process is a very time-consuming task that should be automated as much as possible.</p> <p>Results</p> <p>GeneBrowser is a web-based tool that, for a given list of genes, combines data from several public databases with visualisation and analysis methods to help identify the most relevant and common biological characteristics. The functionalities provided include the following: a central point with the most relevant biological information for each inserted gene; a list of the most related papers in PubMed and gene expression studies in ArrayExpress; and an extended approach to functional analysis applied to Gene Ontology, homologies, gene chromosomal localisation and pathways.</p> <p>Conclusions</p> <p>GeneBrowser provides a unique entry point to several visualisation and analysis methods, providing fast and easy analysis of a set of genes. GeneBrowser fills the gap between Web portals that analyse one gene at a time and functional analysis tools that are limited in scope and usually desktop-based.</p

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    Human alveolar macrophage metabolism is compromised during Mycobacterium tuberculosis infection

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    Pulmonary macrophages have two distinct ontogenies: long-lived embryonically-seeded alveolar macrophages (AM) and bone marrow-derived macrophages (BMDM). Here, we show that after infection with a virulent strain of Mycobacterium tuberculosis (H37Rv), primary murine AM exhibit a unique transcriptomic signature characterized by metabolic reprogramming distinct from conventional BMDM. In contrast to BMDM, AM failed to shift from oxidative phosphorylation (OXPHOS) to glycolysis and consequently were unable to control infection with an avirulent strain (H37Ra). Importantly, healthy human AM infected with H37Ra equally demonstrated diminished energetics, recapitulating our observation in the murine model system. However, the results from seahorse showed that the shift towards glycolysis in both AM and BMDM was inhibited by H37Rv. We further demonstrated that pharmacological (e.g. metformin or the iron chelator desferrioxamine) reprogramming of AM towards glycolysis reduced necrosis and enhanced AM capacity to control H37Rv growth. Together, our results indicate that the unique bioenergetics of AM renders these cells a perfect target for Mtb survival and that metabolic reprogramming may be a viable host targeted therapy against TB

    Dynamic probe selection for studying microbial transcriptome with high-density genomic tiling microarrays

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    <p>Abstract</p> <p>Background</p> <p>Current commercial high-density oligonucleotide microarrays can hold millions of probe spots on a single microscopic glass slide and are ideal for studying the transcriptome of microbial genomes using a tiling probe design. This paper describes a comprehensive computational pipeline implemented specifically for designing tiling probe sets to study microbial transcriptome profiles.</p> <p>Results</p> <p>The pipeline identifies every possible probe sequence from both forward and reverse-complement strands of all DNA sequences in the target genome including circular or linear chromosomes and plasmids. Final probe sequence lengths are adjusted based on the maximal oligonucleotide synthesis cycles and best isothermality allowed. Optimal probes are then selected in two stages - sequential and gap-filling. In the sequential stage, probes are selected from sequence windows tiled alongside the genome. In the gap-filling stage, additional probes are selected from the largest gaps between adjacent probes that have already been selected, until a predefined number of probes is reached. Selection of the highest quality probe within each window and gap is based on five criteria: sequence uniqueness, probe self-annealing, melting temperature, oligonucleotide length, and probe position.</p> <p>Conclusions</p> <p>The probe selection pipeline evaluates global and local probe sequence properties and selects a set of probes dynamically and evenly distributed along the target genome. Unique to other similar methods, an exact number of non-redundant probes can be designed to utilize all the available probe spots on any chosen microarray platform. The pipeline can be applied to microbial genomes when designing high-density tiling arrays for comparative genomics, ChIP chip, gene expression and comprehensive transcriptome studies.</p

    The Healthgrid White Paper

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