11 research outputs found

    Proceedings of the Linux Audio Conference 2018

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    These proceedings contain all papers presented at the Linux Audio Conference 2018. The conference took place at c-base, Berlin, from June 7th - 10th, 2018 and was organized in cooperation with the Electronic Music Studio at TU Berlin

    Finding Our Way through Phenotypes

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    Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility

    Rating model arbitrage in CDO markets: An empirical analysis

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    We analyze whether information asymmetry between issuers and investors leads to rating model arbitrage in Collateralized Debt Obligation markets. Rating model arbitrage is defined as the issuer's deliberate capitalization of information asymmetry at the investor's cost on the basis of different rating processes. Using data from CDO transactions grouped by both rating agencies and underlying rating methodologies, we test for homogeneity of characteristic transaction features within the group and heterogeneity between the different groups. We find that the hypothesis stating non-existence of rating model arbitrage on the basis of information asymmetry does not hold as individual patterns of transaction characteristics within each group could be identified.Rating model arbitrage Collateralized Debt Obligations Asymmetric information

    Digital Transformation in Higher Education: Selection, Test and Acquisition of a Business Support System - Experiences from the Field and Lessons Learned

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    Digital transformation in Higher Education and Science is a mission-critical demand to prepare educational institutions for their future competition on the international market. In many cases, the digitization goes along with the search for and acquisition of new software. For easily exchangeable software, wrong product decisions, in the worst case, lead to calculable financial losses. However, if a planned software requires a lot of technological adjustments and is to be applied as central component of a business- and/or security-critical environment, wrong decisions during the software acquisition process might lead to hardly calculable damage. Questions arising are how to decide for a product and how many resources should be invested for the acquisition process. We planned to apply a commercial Business Support System, which should replace the currently used in-house developed software. Our goals were the increase of our university’s level of data security, to ease the interaction between stakeholders, to eliminate media discontinuities, to improve the process management and transparency, and to reduce the execution time of automated processes. Alongside with the introduction of the electronic case file, our agenda stipulates the digitization (and automation) of administrative university processes, especially, but not limited to, the student self-service and the administrative student life cycle. Usual tools and practices, commonly applied to (simple) software acquisition, failed in our scenario. With the case study introduced in this paper, we address all persons, involved within software acquisition processes: From our experiences, we strongly recommend to place greater value on an exhaustively completed acquisition process, than on short-termed economic advantages

    How to discover branching phenotypes?

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    <p>(Bottom panel) Phenotype data exhibiting various forms of branchiness are not easily discerned from diverse natural language descriptions. (A) Bee hairs are different from most other insect hairs in that they are plumose, which facilitates pollen collection. (B) A mutant of <i>Drosophila melanogaster</i> exhibits forked bristles, due to a variation in <i>mical</i>. (C) In zebrafish larvae (<i>Danio rerio</i>), angiogenesis begins with vessels branching. (D) Plant trichomes take on many forms, including trifurcation. (Top) Phenotypes involving some type of “branched” are easily recovered when they are represented with ontologies. In a semantic graph, free text descriptions are converted into phenotype statements involving an anatomy term from animal or plant ontologies <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Haendel1" target="_blank">[56]</a>,<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Cooper1" target="_blank">[118]</a> and a quality term from a quality ontology <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Gkoutos1" target="_blank">[106]</a>, connected by a logical expression (“inheres_in some”). Anatomy (purple) and quality (green) terms (ontology IDs beneath) relate phenotype statements from different species by virtue of the logic inherent in the ontologies, e.g., plumose, bifurcated, branched, and tripartite are all subtypes of “branched.” Image credits: bumble bee with pollen by Thomas Bresson, seta with pollen by István Mikó, <i>Arabidopsis</i> plants with hair-like structures (trichomes) by Annkatrin Rose, <i>Drosophila</i> photo by John Tann, <i>Drosophila</i> bristles redrawn from <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Hung1" target="_blank">[119]</a>, scanning electron micrograph of <i>Arabidopsis</i> trichome by István Mikó, zebrafish embryos by MichianaSTEM, zebrafish blood vessels from <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Alvarez1" target="_blank">[120]</a>. Figure assembled by Anya Broverman-Wray.</p

    Phenotypes shared across biology.

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    <p>Phenotype data are relevant to many different domains, but they are currently isolated in data “silos.” Research from a broad array of seemingly disconnected domains, as outlined here, can be dramatically accelerated with a computable data store. (<b>A</b>) <b>Domains</b>: Diverse fields such as evolutionary biology, human disease and medicine, and climate change relate to phenotypes. (<b>B</b>) <b>Phenotypes</b>: insects, vertebrates, plants, and even forests all have features that are branched in some way, but they are described using different terms. For a computer to discover this, the phenotypes must be annotated with unique identifiers from ontologies that are logically linked. Under “shape” in the PATO quality ontology <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Gkoutos1" target="_blank">[106]</a>, “branchiness” is an encompassing parent term with subtypes “branched” and “increased branchiness.” From left to right, top layer, insects, vertebrates and plants have species that demonstrate phenotypes for which the genetic basis is not known. Often their companion model species, however, have experimental genetic work that is relevant to proposing candidate genes and gene networks. Insects (1): An evolutionary novelty in bees (top layer) is the presence of branched setae used for pollen collection. Nothing is known about the genetic basis of this feature. One clue to the origin of this evolutionary feature comes from studies of <i>Drosophila</i> (bottom layer), where <i>Mical</i> overexpression in unbranched wild-type bristles generates a branched morphology <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Hung1" target="_blank">[119]</a>. Mical directly links semaphorins and their plexin receptors to the precise control of actin filament dynamics <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Hung1" target="_blank">[119]</a>. Vertebrates (2): In humans, aberrant angiogenesis, including excessive blood vessel branching (top layer), is one of the six central hallmarks of cancer <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Hanahan1" target="_blank">[121]</a>. Candidate genes have been identified using data from model organisms. In zebrafish (middle layer), studies of the control of sprouting in blood vessel development show that signaling via semaphorins <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Yazdani1" target="_blank">[122]</a> and their plexin receptors is required for proper abundance and distribution <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Gu1" target="_blank">[123]</a>; disruption of <i>plxnd1</i> results in increased branching <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Alvarez1" target="_blank">[120]</a>,<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Zygmunt1" target="_blank">[124]</a>,<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-TorresVazquez1" target="_blank">[125]</a>. In mouse (bottom layer), branching of salivary glands is dependent on semaphorin signaling <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Chung1" target="_blank">[126]</a>, as is the branching of various other epithelial organs <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Korostylev1" target="_blank">[127]</a>. Plants (3): The uppermost canopy of trees of the rainforest (top layer) undergo a marked increase in branching associated with climate change <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Niinemets1" target="_blank">[128]</a>. Nothing is known about the genetic basis of this feature. The branching of plant trichomes (bottom layer), tiny outgrowths with a variety of functions including seed dispersal, has been studied in the model <i>Arabidopsis thaliana.</i> Branching occurs in association with many MYB-domain genes <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Serna1" target="_blank">[129]</a>, transcription factors that are found in both plants and animals <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Rosinski1" target="_blank">[130]</a>. (<b>C</b>) <b>Environment</b>: Diverse input from the environment influences organismal phenotype. (<b>D</b>) <b>Genes</b>: At the genetic level, previously unknown associations with various types of “branchiness” between insects and vertebrates are here made to possibly a common core or network of genes (the semaphorin-plexin signaling network). No association between genes associated with plant branching (Myb transcription factors) and animal branching is obvious from the literature. Image credit: Anya Broverman-Wray.</p

    Finding phenotypes.

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    <p>The rich legacy of research in the life sciences includes a wealth of phenotype data contained in many sources, for millions of extinct and extant species. Some important sources of phenotypes date from more than 250 years ago <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-AristotleBalme1" target="_blank">[74]</a>–<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Darwin1" target="_blank">[77]</a>. With very few exceptions, phenotype data are not computationally accessible <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Ramrez2" target="_blank">[78]</a>.</p><p>Finding phenotypes.</p
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