Sandra Gesing

VectorBase: an updated bioinformatics resource for invertebrate vectors and other organisms related with human diseases

VectorBase is a National Institute of Allergy and Infectious Diseases supported Bioinformatics Resource Center (BRC) for invertebrate vectors of human pathogens. Now in its 11th year, VectorBase currently hosts the genomes of 35 organisms including a number of non-vectors for comparative analysis. Hosted data range from genome assemblies with annotated gene features, transcript and protein expression data to population genetics including variation and insecticide-resistance phenotypes. Here we describe improvements to our resource and the set of tools available for interrogating and accessing BRC data including the integration of Web Apollo to facilitate community annotation and providing Galaxy to support user-based workflows. VectorBase also actively supports our community through hands-on workshops and online tutorials. All information and data are freely available from our website at https://www.vectorbase.org/.

Managing, analysing, and integrating big data in medical bioinformatics: open problems and future perspectives.

The explosion of the data both in the biomedical research and in the healthcare systems demands urgent solutions. In particular, the research in omics sciences is moving from a hypothesis-driven to a data-driven approach. Healthcare is additionally always asking for a tighter integration with biomedical data in order to promote personalized medicine and to provide better treatments. Efficient analysis and interpretation of Big Data opens new avenues to explore molecular biology, new questions to ask about physiological and pathological states, and new ways to answer these open issues. Such analyses lead to better understanding of diseases and development of better and personalized diagnostics and therapeutics. However, such progresses are directly related to the availability of new solutions to deal with this huge amount of information. New paradigms are needed to store and access data, for its annotation and integration and finally for inferring knowledge and making it available to researchers. Bioinformatics can be viewed as the “glue” for all these processes. A clear awareness of present high performance computing (HPC) solutions in bioinformatics, Big Data analysis paradigms for computational biology, and the issues that are still open in the biomedical and healthcare fields represent the starting point to win this challenge.

Standards-based metadata management for molecular simulations

State‐of‐the‐art research in a variety of natural sciences depends heavily on methods of computational chemistry, for example, the calculation of the properties of materials, proteins, catalysts, and drugs. Applications providing such methods require a lot of expertise to handle their complexity and the usage of high‐performance computing. The MoSGrid (molecular simulation grid) infrastructure relieves this burden from scientists by providing a science gateway, which eases access to and usage of computational chemistry applications. One of its cornerstones is the molecular simulations markup language (MSML), an extension of the chemical markup language. MSML abstracts all chemical as well as computational aspects of simulations. An application and its results can be described with common semantics. Using such application, independent descriptions users can easily switch between different applications or compare them. This paper introduces MSML, its integration into a science gateway, and its usage for molecular dynamics, quantum chemistry, and protein docking. Copyright

Quantum chemical meta-workflows in MoSGrid

Quantum chemical workflows can be built up within the science gateway Molecular Simulation Grid. Complex workflows required by the end users are dissected into smaller workflows that can be combined freely to larger meta‐workflows. General quantum chemical workflows are described here as well as the real use case of a spectroscopic analysis resulting in an end‐user desired meta‐workflow. All workflow features are implemented via Web Services Parallel Grid Runtime and Developer Environment and submitted to UNICORE. The workflows are stored in the Molecular Simulation Grid repository and ported to the SHIWA repository. Copyright

Workflows in a dashboard: a new generation of usability

In the last 20 years quite a few mature workflow engines and workflow editors have been developed to support communities in managing workflows. While there is a trend followed by the providers of workflow engines to ease the creation of workflows tailored to their specific workflow system, the management tools still often necessitate much understanding of the workflow concepts and languages. This paper describes the approach targeting various workflow systems and building a single user interface for editing and monitoring workflows under consideration of aspects such as optimization and provenance of data. The design allots agile Web frameworks and novel technologies to build a workflow dashboard offered in a web browser and connecting seamlessly to available workflow systems and external resources like Cloud infrastructures. The user interface eliminates the need to become acquainted with diverse layouts. Thus, the usability is immensely increased for various aspects of managing workflows.

Developing science gateways for drug discovery in a grid environment

BackgroundMethods for in silico screening of large databases of molecules increasingly complement and replace experimental techniques to discover novel compounds to combat diseases. As these techniques become more complex and computationally costly we are faced with an increasing problem to provide the research community of life sciences with a convenient tool for high-throughput virtual screening on distributed computing resources.ResultsTo this end, we recently integrated the biophysics-based drug-screening program FlexScreen into a service, applicable for large-scale parallel screening and reusable in the context of scientific workflows.ConclusionsOur implementation is based on Pipeline Pilot and Simple Object Access Protocol and provides an easy-to-use graphical user interface to construct complex workflows, which can be executed on distributed computing resources, thus accelerating the throughput by several orders of magnitude.

From the desktop to the grid: scalable bioinformatics via workflow conversion

BackgroundReproducibility is one of the tenets of the scientific method. Scientific experiments often comprise complex data flows, selection of adequate parameters, and analysis and visualization of intermediate and end results. Breaking down the complexity of such experiments into the joint collaboration of small, repeatable, well defined tasks, each with well defined inputs, parameters, and outputs, offers the immediate benefit of identifying bottlenecks, pinpoint sections which could benefit from parallelization, among others. Workflows rest upon the notion of splitting complex work into the joint effort of several manageable tasks.There are several engines that give users the ability to design and execute workflows. Each engine was created to address certain problems of a specific community, therefore each one has its advantages and shortcomings. Furthermore, not all features of all workflow engines are royalty-free —an aspect that could potentially drive away members of the scientific community.ResultsWe have developed a set of tools that enables the scientific community to benefit from workflow interoperability. We developed a platform-free structured representation of parameters, inputs, outputs of command-line tools in so-called Common Tool Descriptor documents. We have also overcome the shortcomings and combined the features of two royalty-free workflow engines with a substantial user community: the Konstanz Information Miner, an engine which we see as a formidable workflow editor, and the Grid and User Support Environment, a web-based framework able to interact with several high-performance computing resources. We have thus created a free and highly accessible way to design workflows on a desktop computer and execute them on high-performance computing resources.ConclusionsOur work will not only reduce time spent on designing scientific workflows, but also make executing workflows on remote high-performance computing resources more accessible to technically inexperienced users. We strongly believe that our efforts not only decrease the turnaround time to obtain scientific results but also have a positive impact on reproducibility, thus elevating the quality of obtained scientific results.

Science gateway workshops 2014 special issue conference publications

Science gateways are a solution for user communities to access applications and data via a graphical user interface. These graphical user interfaces hide the underlying infrastructure, as far as feasible and as far as desired by the users. In general, science gateways offer a single point of entry to create and/or analyze domain-specific data. Their core goal is to increase the usability and accessibility of computational tools and digitized data as well as to leverage reproducibility of scientific processes. While the user interfaces are especially tailored to the specific demands of a user community, the underlying infrastructures, for example, national or international distributed computing infrastructures (e.g., XSEDE), are mainly applicable for a wide range of use cases. Thus, science gateway frameworks and science gateway APIs, which offer building blocks for the management of jobs and data within such infrastructures, ease the implementation of science gateways for developers. The latter can focus on the domain-specific demands while reusing or extending available building blocks. The contributions to this special issue present the current state-of-the-art research and elucidate trends in the area of science gateways as well as demonstrate available solutions for the users. Submissions are grouped in five general areas: science gateway use and sustainability, generic development frameworks, novel workflow-oriented approaches, data management, and use cases from diverse domains. The statistics illuminate among other topics the increased usage of science gateways, which is also reflected in high number of submissions demonstrating specific use cases. Consequently, sustainability approaches have found their way into the special issue reflected not only in a submission about a model for sustainability but also in numerous submissions on developments and enhancements for generic building blocks of diverse existing mature science gateway frameworks and APIs. While novel approaches for workflow management and data management can be also considered under the enhancements for generic building blocks addressing new technologies such as mobile applications, they have already been core subjects for a couple of years and are presented in own sections emphasizing their importance for the science gateway community.

Meta-Metaworkflows for Combining Quantum Chemistry and Molecular Dynamics in the MoSGrid Science Gateway

MoSGrid (Molecular Simulation Grid) is a user-friendly and highly efficient science gateway which contains three domains for the different methodologies used in chemistry: quantum chemistry, molecular dynamics, and docking. Workflows are implemented by using the WS-PGRADE technology. By adding an abstraction layer, we are able to develop meta-metaworkflows for quantum chemical applications and a combination between quantum chemical and molecular dynamics applications. This approach allows researchers to easily and more quickly create highly complex workflows allowing them to shorten the time-to-result considerably.

Using Science Gateways for Bridging the Differences between Research Infrastructures

Researchers can perform large-scale analyses on diverse computing and data infrastructures such as NGIs (National Grid Infrastructures), XSEDE (Extreme Science and Engineering Discovery Environment) and PRACE (Partnership for Advanced Computing in Europe). Some are national like NGIs and XSEDE, some are international like PRACE and all of them require a more or less restrictive application process to get access to resources. Science gateways integrating diverse infrastructures provide the possibility to re-use methods independent of such underlying infrastructures and thus potentially deliver the technical prerequisite for creating reproducible science. To achieve this goal, science gateways have to be integrated seamlessly with security mechanisms and job, data as well as workflow management of the targeted resources. This paper gives an overview on general findings for porting science gateways as well as the challenges faced for porting the German MoSGrid science gateway (Molecular Simulation Grid) to exploit XSEDE and PRACE infrastructures.