MOTIVATION: Ribosome profiling, or Ribo-seq, is the state-of-the-art method for quantifying protein synthesis in living cells. Computational analysis of Ribo-seq data remains challenging due to the complexity of the procedure, as well as variations introduced for specific organisms or specialized analyses. RESULTS: We present riboviz 2, an updated riboviz package, for the comprehensive transcript-centric analysis and visualization of Ribo-seq data. riboviz 2 includes an analysis workflow built on the Nextflow workflow management system for end-to-end processing of Ribo-seq data. riboviz 2 has been extensively tested on diverse species and library preparation strategies, including multiplexed samples. riboviz 2 is flexible and uses open, documented file formats, allowing users to integrate new analyses with the pipeline. AVAILABILITY AND IMPLEMENTATION: riboviz 2 is freely available at github.com/riboviz/riboviz.

Workflow management systems represent, manage, and execute multistep computational analyses and offer many benefits to bioinformaticians. They provide a common language for describing analysis workflows, contributing to reproducibility and to building libraries of reusable components. They can support both incremental build and re-entrancy-the ability to selectively re-execute parts of a workflow in the presence of additional inputs or changes in configuration and to resume execution from where a workflow previously stopped. Many workflow management systems enhance portability by supporting the use of containers, high-performance computing (HPC) systems, and clouds. Most importantly, workflow management systems allow bioinformaticians to delegate how their workflows are run to the workflow management system and its developers. This frees the bioinformaticians to focus on what these workflows should do, on their data analyses, and on their science. RiboViz is a package to extract biological insight from ribosome profiling data to help advance understanding of protein synthesis. At the heart of RiboViz is an analysis workflow, implemented in a Python script. To conform to best practices for scientific computing which recommend the use of build tools to automate workflows and to reuse code instead of rewriting it, the authors reimplemented this workflow within a workflow management system. To select a workflow management system, a rapid survey of available systems was undertaken, and candidates were shortlisted: Snakemake, cwltool, Toil, and Nextflow. Each candidate was evaluated by quickly prototyping a subset of the RiboViz workflow, and Nextflow was chosen. The selection process took 10 person-days, a small cost for the assurance that Nextflow satisfied the authors' requirements. The use of prototyping can offer a low-cost way of making a more informed selection of software to use within projects, rather than relying solely upon reviews and recommendations by others.

With the increasing popularity of the cloud computing model and rapid proliferation of cloud infrastructures there are increasing concerns about energy consumption and consequent impact of cloud computing as a contributor to global CO2emissions. To date, little is known about how to incorporate energy consumption and CO2concerns into cloud application development and deployment decision models. In this respect, this paper describes an eco-aware approach that relies on the definition, monitoring and utilization of energy and CO2metrics combined with the use of innovative application scheduling and runtime adaptation techniques to optimize energy consumption and CO2footprint of cloud applications as well as the underlying infrastructure. The eco-aware approach involves measuring or quantifying the energy consumption and CO2at different levels of cloud computing, using that information to create scheduling and adaptation techniques that contribute towards reducing the energy consumption and CO2emissions, and finally testing and validating the developed solutions in a multi-site cloud environment with the help of challenging case study applications. The experimental and validation results show the potential of the eco-aware approach to significantly reduce the CO2footprint and consequent environmental impact of cloud applications.

BonFIRE is a multi-site test bed that supports testing of Cloud-based and distributed applications. BonFIRE breaks the mould of commercial Cloud offerings by providing unique functionality in terms of observability, control, advanced Cloud features and ease of use for experimentation. A number of successful use cases have been executed on BonFIRE, involving industrial and academic users and delivering impact in diverse areas, such as media, e-health, environment and manufacturing. The BonFIRE user-base is expanding through its free, Open Access scheme, daily carrying out important research, while the consortium is working to sustain the facility beyond 2014.

Abstract The PGPGrid project aims to parallelize the process of extracting range data from an experimental 3D scanner using the Grid as a vehicle for accessing necessary resources. The application is potentially highly parallel but has some unusual features such as rapid spawning of processes in real time and a dynamic inter‐process network topology. These characteristics are such as to require enhancement of the usual task migration capabilities of the Globus toolkit. The present paper initially discusses attempts to estimate the real parallelizability of the scanner application. It then describes a new Java application programming interface, based on Milner's $\pi$ ‐calculus, which could be used to extend Globus in a manner capable of supporting systems with this kind of dynamic parallel structure. The location of processing resources for the $\pi$ ‐calculus is done using a Web‐services‐based resource locator. The article also describes the pipeline of processing from initial stereo photogrametry to the final production of animation models. A key step in this is the conformation of animators models to the data obtained by the real‐time scanner. Algorithmic innovations in this process are described. Copyright © 2006 John Wiley & Sons, Ltd.

Grid application performance is inherently dependent on the performance and reliability of the underlying network. In a production Grid infrastructure, network performance monitoring (NPM) information is required both for middleware resource-brokering decisions and operational monitoring. A variety of NPM frameworks are available which can provide such information. However, the diverse global nature of the EGEE (Enabling Grids for E-sciencE) fabric means it is impractical to mandate a single monitoring solution. In this paper we propose a broker-based federated architecture for integration of NPM information from a heterogeneous set of monitoring frameworks, which provides simplified access to the frameworks for clients. We also present an overview of the requirements for NPM gathered from EGEE middleware developers and operational monitoring users. Finally, we describe our pilot implementation which has proven the validity of the architecture and demonstrated the first integrated access to backbone and end-to-end data gathered using different monitoring frameworks.

Production Grid infrastructure requires end-to- end guarantees on the Quality of Service from the underlying networks. In this paper, we present use cases for advance network resource reservation and then describe a multi-layered architecture that can support them. The architecture presents a single bandwidth broker, called BAR, which sits at the Grid layer. BAR not only provides a single point of access to Grid applications to reserve guaranteed end-to-end bandwidth, but also presents its interface in application terms (instead of networking terms). We expose two guaranteed bandwidth services: the Guaranteed Delivery File Transfer and Virtual Leased Line services. Integrated with the GEANT2 bandwidth on demand infrastructure, our bandwidth broker deals with multiple network domains, further insulating the applications from network concerns. We also define additional components required for an end-to-end reservation as well as the interfaces between the components. Our deployed prototype demonstrated the world's first software-based, inter-domain bandwidth reservations based on Premium IP.