69 research outputs found

    Scaling properties of protein family phylogenies

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    One of the classical questions in evolutionary biology is how evolutionary processes are coupled at the gene and species level. With this motivation, we compare the topological properties (mainly the depth scaling, as a characterization of balance) of a large set of protein phylogenies with a set of species phylogenies. The comparative analysis shows that both sets of phylogenies share remarkably similar scaling behavior, suggesting the universality of branching rules and of the evolutionary processes that drive biological diversification from gene to species level. In order to explain such generality, we propose a simple model which allows us to estimate the proportion of evolvability/robustness needed to approximate the scaling behavior observed in the phylogenies, highlighting the relevance of the robustness of a biological system (species or protein) in the scaling properties of the phylogenetic trees. Thus, the rules that govern the incapability of a biological system to diversify are equally relevant both at the gene and at the species level.Comment: Replaced with final published versio

    Reviewing the integration of patient data: how systems are evolving in practice to meet patient needs

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    <p>Abstract</p> <p>Background</p> <p>The integration of Information Systems (IS) is essential to support shared care and to provide consistent care to individuals – patient-centred care. This paper identifies, appraises and summarises studies examining different approaches to integrate patient data from heterogeneous IS.</p> <p>Methods</p> <p>The literature was systematically reviewed between 1995–2005 to identify articles mentioning patient records, computers and data integration or sharing.</p> <p>Results</p> <p>Of 3124 articles, 84 were included describing 56 distinct projects. Most of the projects were on a regional scale. Integration was most commonly accomplished by messaging with pre-defined templates and middleware solutions. HL7 was the most widely used messaging standard. Direct database access and web services were the most common communication methods. The user interface for most systems was a Web browser. Regarding the type of medical data shared, 77% of projects integrated diagnosis and problems, 67% medical images and 65% lab results. More recently significantly more IS are extending to primary care and integrating referral letters.</p> <p>Conclusion</p> <p>It is clear that Information Systems are evolving to meet people's needs by implementing regional networks, allowing patient access and integration of ever more items of patient data. Many distinct technological solutions coexist to integrate patient data, using differing standards and data architectures which may difficult further interoperability.</p

    Extracting phylogenetic signal and accounting for bias in whole-genome data sets supports the Ctenophora as sister to remaining Metazoa

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    BACKGROUND: Understanding the phylogenetic relationships among major lineages of multicellular animals (the Metazoa) is a prerequisite for studying the evolution of complex traits such as nervous systems, muscle tissue, or sensory organs. Transcriptome-based phylogenies have dramatically improved our understanding of metazoan relationships in recent years, although several important questions remain. The branching order near the base of the tree, in particular the placement of the poriferan (sponges, phylum Porifera) and ctenophore (comb jellies, phylum Ctenophora) lineages is one outstanding issue. Recent analyses have suggested that the comb jellies are sister to all remaining metazoan phyla including sponges. This finding is surprising because it suggests that neurons and other complex traits, present in ctenophores and eumetazoans but absent in sponges or placozoans, either evolved twice in Metazoa or were independently, secondarily lost in the lineages leading to sponges and placozoans. RESULTS: To address the question of basal metazoan relationships we assembled a novel dataset comprised of 1080 orthologous loci derived from 36 publicly available genomes representing major lineages of animals. From this large dataset we procured an optimized set of partitions with high phylogenetic signal for resolving metazoan relationships. This optimized data set is amenable to the most appropriate and computationally intensive analyses using site-heterogeneous models of sequence evolution. We also employed several strategies to examine the potential for long-branch attraction to bias our inferences. Our analyses strongly support the Ctenophora as the sister lineage to other Metazoa. We find no support for the traditional view uniting the ctenophores and Cnidaria. Our findings are supported by Bayesian comparisons of topological hypotheses and we find no evidence that they are biased by long-branch attraction. CONCLUSIONS: Our study further clarifies relationships among early branching metazoan lineages. Our phylogeny supports the still-controversial position of ctenophores as sister group to all other metazoans. This study also provides a workflow and computational tools for minimizing systematic bias in genome-based phylogenetic analyses. Future studies of metazoan phylogeny will benefit from ongoing efforts to sequence the genomes of additional invertebrate taxa that will continue to inform our view of the relationships among the major lineages of animals. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-2146-4) contains supplementary material, which is available to authorized users

    Measures of frailty in population-based studies: An overview

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    Although research productivity in the field of frailty has risen exponentially in recent years, there remains a lack of consensus regarding the measurement of this syndrome. This overview offers three services: first, we provide a comprehensive catalogue of current frailty measures; second, we evaluate their reliability and validity; third, we report on their popularity of use

    Research Trends in Medical Imaging Informatics

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