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The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

Plant breeders and educators working with the International Potato Center (CIP) needed freely available statistical tools. In response, we created first a set of scripts for specific tasks using the open source statistical software R. Based on this we eventually compiled the R package agricolae as it covered a niche. Here we describe for the first time its main functions in the form of an article. We also review its reception using download statistics, citation data, and feedback from a user survey. We highlight usage in our extended network of collaborators. The package has found applications beyond agriculture in fields like aquaculture, ecology, biodiversity, conservation biology and cancer research. In summary, the package agricolae is a well established statistical toolbox based on R with a broad range of applications in design and analyses of experiments also in the wider biological community .

We report the first identification of novel viruses, and sequence of an entire viral genome, by a single step of high-throughput parallel sequencing of small RNAs from diseased, as well as symptomless plants. Contigs were assembled from sequenced total siRNA from plants using small sequence assembly software and could positively identify RNA, ssDNA and dsDNA reverse transcribing viruses and in one case spanned the entire genome. The results present a novel approach which cannot only identify known viral pathogens, occurring at extremely low titers, but also novel viruses, without the necessity of any prior knowledge.

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