55 research outputs found

    Reconciliation Revisited: Handling Multiple Optima when Reconciling with Duplication, Transfer, and Loss

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    Phylogenetic tree reconciliation is a powerful approach for inferring evolutionary events like gene duplication, horizontal gene transfer, and gene loss, which are fundamental to our understanding of molecular evolution. While duplication–loss (DL) reconciliation leads to a unique maximum-parsimony solution, duplication-transfer-loss (DTL) reconciliation yields a multitude of optimal solutions, making it difficult to infer the true evolutionary history of the gene family. This problem is further exacerbated by the fact that different event cost assignments yield different sets of optimal reconciliations. Here, we present an effective, efficient, and scalable method for dealing with these fundamental problems in DTL reconciliation. Our approach works by sampling the space of optimal reconciliations uniformly at random and aggregating the results. We show that even gene trees with only a few dozen genes often have millions of optimal reconciliations and present an algorithm to efficiently sample the space of optimal reconciliations uniformly at random in O(mn[superscript 2]) time per sample, where m and n denote the number of genes and species, respectively. We use these samples to understand how different optimal reconciliations vary in their node mappings and event assignments and to investigate the impact of varying event costs. We apply our method to a biological dataset of approximately 4700 gene trees from 100 taxa and observe that 93% of event assignments and 73% of mappings remain consistent across different multiple optima. Our analysis represents the first systematic investigation of the space of optimal DTL reconciliations and has many important implications for the study of gene family evolution.National Science Foundation (U.S.) (CAREER Award 0644282)National Institutes of Health (U.S.) (Grant RC2 HG005639)National Science Foundation (U.S.). Assembling the Tree of Life (Program) (Grant 0936234

    Beyond representing orthology relations by trees

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    Reconstructing the evolutionary past of a family of genes is an important aspect of many genomic studies. To help with this, simple relations on a set of sequences called orthology relations may be employed. In addition to being interesting from a practical point of view they are also attractive from a theoretical perspective in that e.\,g.\,a characterization is known for when such a relation is representable by a certain type of phylogenetic tree. For an orthology relation inferred from real biological data it is however generally too much to hope for that it satisfies that characterization. Rather than trying to correct the data in some way or another which has its own drawbacks, as an alternative, we propose to represent an orthology relation δ\delta in terms of a structure more general than a phylogenetic tree called a phylogenetic network. To compute such a network in the form of a level-1 representation for δ\delta, we formalize an orthology relation in terms of the novel concept of a symbolic 3- dissimilarity which is motivated by the biological concept of a ``cluster of orthologous groups'', or COG for short. For such maps which assign symbols rather that real values to elements, we introduce the novel {\sc Network-Popping} algorithm which has several attractive properties. In addition, we characterize an orthology relation δ\delta on some set XX that has a level-1 representation in terms of eight natural properties for δ\delta as well as in terms of level-1 representations of orthology relations on certain subsets of XX

    Assessing hospitals' clinical risk management: Development of a monitoring instrument

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    <p>Abstract</p> <p>Background</p> <p>Clinical risk management (CRM) plays a crucial role in enabling hospitals to identify, contain, and manage risks related to patient safety. So far, no instruments are available to measure and monitor the level of implementation of CRM. Therefore, our objective was to develop an instrument for assessing CRM in hospitals.</p> <p>Methods</p> <p>The instrument was developed based on a literature review, which identified key elements of CRM. These elements were then discussed with a panel of patient safety experts. A theoretical model was used to describe the level to which CRM elements have been implemented within the organization. Interviews with CRM practitioners and a pilot evaluation were conducted to revise the instrument. The first nationwide application of the instrument (138 participating Swiss hospitals) was complemented by in-depth interviews with 25 CRM practitioners in selected hospitals, for validation purposes.</p> <p>Results</p> <p>The monitoring instrument consists of 28 main questions organized in three sections: 1) Implementation and organizational integration of CRM, 2) Strategic objectives and operational implementation of CRM at hospital level, and 3) Overview of CRM in different services. The instrument is available in four languages (English, German, French, and Italian). It allows hospitals to gather comprehensive and systematic data on their CRM practice and to identify areas for further improvement.</p> <p>Conclusions</p> <p>We have developed an instrument for assessing development stages of CRM in hospitals that should be feasible for a continuous monitoring of developments in this important area of patient safety.</p

    Evolution of protein domain architectures

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    This chapter reviews current research on how protein domain architectures evolve. We begin by summarizing work on the phylogenetic distribution of proteins, as this will directly impact which domain architectures can be formed in different species. Studies relating domain family size to occurrence have shown that they generally follow power law distributions, both within genomes and larger evolutionary groups. These findings were subsequently extended to multi-domain architectures. Genome evolution models that have been suggested to explain the shape of these distributions are reviewed, as well as evidence for selective pressure to expand certain domain families more than others. Each domain has an intrinsic combinatorial propensity, and the effects of this have been studied using measures of domain versatility or promiscuity. Next, we study the principles of protein domain architecture evolution and how these have been inferred from distributions of extant domain arrangements. Following this, we review inferences of ancestral domain architecture and the conclusions concerning domain architecture evolution mechanisms that can be drawn from these. Finally, we examine whether all known cases of a given domain architecture can be assumed to have a single common origin (monophyly) or have evolved convergently (polyphyly). We end by a discussion of some available tools for computational analysis or exploitation of protein domain architectures and their evolution

    Planning and Managing the Safety System (2nd edition, due November 2016)

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    Safety and Health Management Planning addresses new regulations and practices to help you achieve safety and health management success. Emphasizing the reduction of costs through cost/benefit analysis, this book covers practical material and real-world examples of common exercises, including safety measurement and benchmarking, economic design analysis, total quality management and planning, budgeting, and using audits and safety committees effectively. --Publisher\u27s websit

    Measuring and Evaluating Safety Management System Effectiveness Using Data Envelopment Analysis

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    In January 2015, the FAA released a congressionally mandated, final rule on Safety Management Systems (SMS) for Part 121 air carriers. Since organizations must implement SMS, often at considerable expense, a sound, valid means of measuring SMS effectiveness must be established. The purpose of this research was to develop a model to measure and test SMS effectiveness. It was constructed through a systematic series of steps, ensuring accomplishment of research objectives. While preliminary, this research demonstrates that Data Envelopment Analysis (DEA) models can be produced to help organizations measure the effectiveness of their SMS and determine how to improve SMS-related performance
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