SUMMARY: The existence of more than 100 public Galaxy servers with service quotas is indicative of the need for an increased availability of compute resources for Galaxy to use. The GalaxyCloudRunner enables a Galaxy server to easily expand its available compute capacity by sending user jobs to cloud resources. User jobs are routed to the acquired resources based on a set of configurable rules and the resources can be dynamically acquired from any of four popular cloud providers (AWS, Azure, GCP or OpenStack) in an automated fashion. AVAILABILITY AND IMPLEMENTATION: GalaxyCloudRunner is implemented in Python and leverages Docker containers. The source code is MIT licensed and available at https://github.com/cloudve/galaxycloudrunner. The documentation is available at http://gcr.cloudve.org/.

What does it take to convert a heap of sequencing data into a publishable result? First, common tools are employed to reduce primary data (sequencing reads) to a form suitable for further analyses (i.e., the list of variable sites). The subsequent exploratory stage is much more ad hoc and requires the development of custom scripts and pipelines, making it problematic for biomedical researchers. Here, we describe a hybrid platform combining common analysis pathways with the ability to explore data interactively. It aims to fully encompass and simplify the "raw data-to-publication" pathway and make it reproducible.

Summary Fueled by the radically increased capacity to generate data over the past decade, the field of biomedical research has been constrained by the ability to analyze data. Galaxy, a Web‐based, open‐source data integration and analysis platform for life science research, has been democratizing access to data analysis tools. However, the scale of data and the scope of tools required have proven to be a significant challenge for any monolithic deployment of the Galaxy application. We have found that a distributed and federated approach to utilizing compute and storage resources is necessary. This paper describes the ongoing efforts in creating a ubiquitous platform capable of simultaneously utilizing dedicated as well as on‐demand cloud resources. Specifically, the requirements, process, and an implementation of a cloud‐bursting system are detailed. Copyright © 2010 John Wiley & Sons, Ltd.

BACKGROUND: Computational biology comprises a wide range of technologies and approaches. Multiple technologies can be combined to create more powerful workflows if the individuals contributing the data or providing tools for its interpretation can find mutual understanding and consensus. Much conversation and joint investigation are required in order to identify and implement the best approaches. Traditionally, scientific conferences feature talks presenting novel technologies or insights, followed up by informal discussions during coffee breaks. In multi-institution collaborations, in order to reach agreement on implementation details or to transfer deeper insights in a technology and practical skills, a representative of one group typically visits the other. However, this does not scale well when the number of technologies or research groups is large. Conferences have responded to this issue by introducing Birds-of-a-Feather (BoF) sessions, which offer an opportunity for individuals with common interests to intensify their interaction. However, parallel BoF sessions often make it hard for participants to join multiple BoFs and find common ground between the different technologies, and BoFs are generally too short to allow time for participants to program together. RESULTS: This report summarises our experience with computational biology Codefests, Hackathons and Sprints, which are interactive developer meetings. They are structured to reduce the limitations of traditional scientific meetings described above by strengthening the interaction among peers and letting the participants determine the schedule and topics. These meetings are commonly run as loosely scheduled "unconferences" (self-organized identification of participants and topics for meetings) over at least two days, with early introductory talks to welcome and organize contributors, followed by intensive collaborative coding sessions. We summarise some prominent achievements of those meetings and describe differences in how these are organised, how their audience is addressed, and their outreach to their respective communities. CONCLUSIONS: Hackathons, Codefests and Sprints share a stimulating atmosphere that encourages participants to jointly brainstorm and tackle problems of shared interest in a self-driven proactive environment, as well as providing an opportunity for new participants to get involved in collaborative projects.

Cloud computing is used to describe a collection of (remote) data centers (the hardware and the software) and applications delivered from them as a service (SaaS, Software as a Service). Its success is driven by the cost-effective on-demand availability of large, scalable amounts of computing resources. The cloud has become an established paradigm for many enterprise and consumer applications such as email, web servers, productivity applications, customer relationship management, etc. However, in IC design its success is still limited.