Martin Senger

BioMoby extensions to the Taverna workflow management and enactment software

BackgroundAs biology becomes an increasingly computational science, it is critical that we develop software tools that support not only bioinformaticians, but also bench biologists in their exploration of the vast and complex data-sets that continue to build from international genomic, proteomic, and systems-biology projects. The BioMoby interoperability system was created with the goal of facilitating the movement of data from one Web-based resource to another to fulfill the requirements of non-expert bioinformaticians. In parallel with the development of BioMoby, the European myGrid project was designing Taverna, a bioinformatics workflow design and enactment tool. Here we describe the marriage of these two projects in the form of a Taverna plug-in that provides access to many of BioMobys features through the Taverna interface.ResultsThe exposed BioMoby functionality aids in the design of sensible BioMoby workflows, aids in pipelining BioMoby and non-BioMoby-based resources, and ensures that end-users need only a minimal understanding of both BioMoby, and the Taverna interface itself. Users are guided through the construction of syntactically and semantically correct workflows through plug-in calls to the Moby Central registry. Moby Central provides a menu of only those BioMoby services capable of operating on the data-type(s) that exist at any given position in the workflow. Moreover, the plug-in automatically and correctly connects a selected service into the workflow such that users are not required to understand the nature of the inputs or outputs for any service, leaving them to focus on the biological meaning of the workflow they are constructing, rather than the technical details of how the services will interoperate.ConclusionWith the availability of the BioMoby plug-in to Taverna, we believe that BioMoby-based Web Services are now significantly more useful and accessible to bench scientists than are more traditional Web Services.

Multifunctional crop trait ontology for breeders' data: field book, annotation, data discovery and semantic enrichment of the literature

The ‘Crop Ontology’ database we describe provides a controlled vocabulary for several economically important crops. It facilitates data integration and discovery from global databases and digital literature. This allows researchers to exploit comparative phenotypic and genotypic information of crops to elucidate functional aspects of traits.

The phenotype and genotype experiment object model (PaGE-OM): a robust data structure for information related to DNA variation

Torrents of genotype–phenotype data are being generated, all of which must be captured, processed, integrated, and exploited. To do this optimally requires the use of standard and interoperable “object models,” providing a description of how to partition the total spectrum of information being dealt with into elemental “objects” (such as “alleles,” “genotypes,” “phenotype values,” “methods”) with precisely stated logical interrelationships (such as “A objects are made up from one or more B objects”). We herein propose the Phenotype and Genotype Experiment Object Model (PaGE‐OM; www.pageom.org), which has been tested and implemented in conjunction with several major databases, and approved as a standard by the Object Management Group (OMG). PaGE‐OM is open‐source, ready for use by the wider community, and can be further developed as needs arise. It will help to improve information management, assist data integration, and simplify the task of informatics resource design and construction for genotype and phenotype data projects.Hum Mutat 30, 968–977, 2009.

The generation challenge programme platform: semantic standards and workbench for crop science.

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making.