Annotation and visualization of endogenous retroviral sequences using the Distributed Annotation System (DAS) and eBioX

<p>Abstract</p> <p>Background</p> <p>The Distributed Annotation System (DAS) is a widely used network protocol for sharing biological information. The distributed aspects of the protocol enable the use of various reference and annotation servers for connecting biological sequence data to pertinent annotations in order to depict an integrated view of the data for the final user.</p> <p>Results</p> <p>An annotation server has been devised to provide information about the endogenous retroviruses detected and annotated by a specialized <it>in silico </it>tool called RetroTector. We describe the procedure to implement the DAS 1.5 protocol commands necessary for constructing the DAS annotation server. We use our server to exemplify those steps. Data distribution is kept separated from visualization which is carried out by eBioX, an easy to use open source program incorporating multiple bioinformatics utilities. Some well characterized endogenous retroviruses are shown in two different DAS clients. A rapid analysis of areas free from retroviral insertions could be facilitated by our annotations.</p> <p>Conclusion</p> <p>The DAS protocol has shown to be advantageous in the distribution of endogenous retrovirus data. The distributed nature of the protocol is also found to aid in combining annotation and visualization along a genome in order to enhance the understanding of ERV contribution to its evolution. Reference and annotation servers are conjointly used by eBioX to provide visualization of ERV annotations as well as other data sources. Our DAS data source can be found in the central public DAS service repository, <url>http://www.dasregistry.org</url>, or at <url>http://loka.bmc.uu.se/das/sources</url>.</p

Stencil Computation Auto-Tuning via Dataflow Graph Transformations

Fine-tuning of optimizations such as loop tiling and array padding is typically required in order to achieve good performance in memory-intensive numerical applications on current computer architectures. Auto-tuning techniques can automate this traditionally laborious task and achieve good performance, but the techniques have so far been application-specific and difficult to adapt to new applications. This thesis investigates developing a framework and language supporting a more general purpose auto-tuner. A high level language capable of expressing programs that deal with multi-dimensional arrays was created to serve as a program representation for use with the auto-tuner. The language is based on the dataflow model where a program is represented as a directed graph describing the flow of data between operations, and uses a novel iteration model based on a hierarchy of flows leading to simple representations of certain loop tiling and parallelization transformations. The iteration construct proved useful by allowing composition of tiling and parallelization transformations, but may not have been a good choice since it made it difficult to validate transformation opportunities. The auto-tuner was evaluated by applying it to a simple stencil computation program. It was confirmed that memory access optimizations do matter for parallel stencil computations on mainstream multicore architectures, and that the impact of optimizations is architecture-dependent. Auto-tuning was shown to be a useful strategy for applying a range of parameterized optimizations. The presented auto-tuner lacks an algorithm for identifying valid optimization opportunities, and must be told what transformations to apply and where to apply them. Still, the use of a high-level dataflow language did simplify auto-tuning by removing the need for writing a program-specific code generator

Stencil Computation Auto-Tuning via Dataflow Graph Transformations

Fine-tuning of optimizations such as loop tiling and array padding is typically required in order to achieve good performance in memory-intensive numerical applications on current computer architectures. Auto-tuning techniques can automate this traditionally laborious task and achieve good performance, but the techniques have so far been application-specific and difficult to adapt to new applications. This thesis investigates developing a framework and language supporting a more general purpose auto-tuner. A high level language capable of expressing programs that deal with multi-dimensional arrays was created to serve as a program representation for use with the auto-tuner. The language is based on the dataflow model where a program is represented as a directed graph describing the flow of data between operations, and uses a novel iteration model based on a hierarchy of flows leading to simple representations of certain loop tiling and parallelization transformations. The iteration construct proved useful by allowing composition of tiling and parallelization transformations, but may not have been a good choice since it made it difficult to validate transformation opportunities. The auto-tuner was evaluated by applying it to a simple stencil computation program. It was confirmed that memory access optimizations do matter for parallel stencil computations on mainstream multicore architectures, and that the impact of optimizations is architecture-dependent. Auto-tuning was shown to be a useful strategy for applying a range of parameterized optimizations. The presented auto-tuner lacks an algorithm for identifying valid optimization opportunities, and must be told what transformations to apply and where to apply them. Still, the use of a high-level dataflow language did simplify auto-tuning by removing the need for writing a program-specific code generator

State of the Nordic Region 2018 : Immigration and integration edition

State of the Nordic Region 2018 Migration and Integration presents a series of facts and figures showing the current state of integration within core socioeconomic sectors, including demography, the labour force, health, and foreign background in state funded culture in the Nordic Region. The report is produced by Nordregio, an international research center for regional development and planning established by the Nordic Council of Ministers, on behalf of Nordic Welfare Centre and the programme Nordic co-operation on integration of refugees and migrants, along with Nordic Agency for Cultural Policy Analysis. The report is partly based on State of the Nordic Region 2018, which is a unique compilation of statistics and maps, giving a detailed view of the Nordic countries at both national and regional level