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Public Comment Period Commences for iPlant Discovery Environment
The iPlant Collaborative is pleased to announce the commencement of the public comment period for the first iPlant Discovery Environment. The Collaborative is creating a cyberinfrastructure (CI) for the plant sciences. One key aspect of this CI is the Discovery Environment, which provides a modern, common web interface and platform to expose the computing, data, and application resources made available to the community. The Discovery Environment will provide access not only to tools built by the collaborative, but to many community-contributed tools as well.
Beginning immediately, users can request access to the technology preview release of the Discovery Environment. The technology preview is a functional snapshot of some features of the architecture thus far, and is intended to give the community a sense of the direction development is taking.
The initial technology preview release provides a working demonstration of a number of architectural features, many of which will not be immediately evident to the user. What users will see is the implementation of a use case for phylogenetic tree data; namely, the ability to run a phylogenetic independent contrast on tree and trait data. This use case includes the incorporation of existing bioinformatics tools seamlessly running on high performance computing (HPC) resources. Users will also experience the underlying features that will enable additional and more complex investigations in the future. These include a secure data management and editing environment, and tree visualization.
Upcoming releases of iPlant's Tree of Life Discovery Environment will include support for inferring and visualizing large phylogenetic trees, a workflow for tree reconciliation, and tools for ancestral character trait reconstruction and taxonomic name resolution. Capabilities for Genotype to Phenotype studies will be incorporated in upcoming releases of the Discovery Environment and initially will provide a workflow for analyzing high throughput sequencing data and tools to visualize complex datasets.