Rice-Map: a new-generation rice genome browser

<p>Abstract</p> <p>Background</p> <p>The concurrent release of rice genome sequences for two subspecies (<it>Oryza sativa </it>L. ssp. <it>japonica </it>and <it>Oryza sativa </it>L. ssp. <it>indica</it>) facilitates rice studies at the whole genome level. Since the advent of high-throughput analysis, huge amounts of functional genomics data have been delivered rapidly, making an integrated online genome browser indispensable for scientists to visualize and analyze these data. Based on next-generation web technologies and high-throughput experimental data, we have developed Rice-Map, a novel genome browser for researchers to navigate, analyze and annotate rice genome interactively.</p> <p>Description</p> <p>More than one hundred annotation tracks (81 for <it>japonica </it>and 82 for <it>indica</it>) have been compiled and loaded into Rice-Map. These pre-computed annotations cover gene models, transcript evidences, expression profiling, epigenetic modifications, inter-species and intra-species homologies, genetic markers and other genomic features. In addition to these pre-computed tracks, registered users can interactively add comments and research notes to Rice-Map as User-Defined Annotation entries. By smoothly scrolling, dragging and zooming, users can browse various genomic features simultaneously at multiple scales. On-the-fly analysis for selected entries could be performed through dedicated bioinformatic analysis platforms such as WebLab and Galaxy. Furthermore, a BioMart-powered data warehouse "Rice Mart" is offered for advanced users to fetch bulk datasets based on complex criteria.</p> <p>Conclusions</p> <p>Rice-Map delivers abundant up-to-date <it>japonica </it>and <it>indica </it>annotations, providing a valuable resource for both computational and bench biologists. Rice-Map is publicly accessible at <url>http://www.ricemap.org/</url>, with all data available for free downloading.</p

Continuous integration for web-based software infrastructures: lessons learned on the webinos project

Testing web-based software infrastructures is challenging. The need to interact with different services running on different devices, with different expectations for security and privacy contributes not only to the complexity of the infrastructure, but also to the approaches necessary to test it. Moreover, as large-scale systems, such infrastructures may be developed by distributed teams simultaneously making changes to APIs and critical components that implement them. In this paper, we describe our experiences testing one such infrastructure – the webinos software platform – and the lessons learned tackling the challenges faced. While ultimately these challenges were impossible to overcome, this paper explores the techniques that worked most effectively and makes recommendations for developers and teams in similar situations. In particular, our experiences with continuous integration and automated testing processes are described and analysed