An Extensible, Scalable Architecture for Managing Bioinformatics Data and Analyses

Shah, Anuj R.; Singhal, Mudita; Gibson, Tara; Sivaramakrishnan, Chandrika; Waters, Katrina M.; Gorton, Ian

doi:10.1109/escience.2008.69

Cited by 9 publications

(5 citation statements)

References 24 publications

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“…MeDICi is a middleware platform for building complex, high performance analytical applications. It has been proven efficient and successful as the communication backbone and execution environment for scientific and analytic domain applications such as atmospheric sciences [4], bioinformatics [25], and cyber security [26].…”

Section: B Framework -Workflow Architecture On Medicimentioning

confidence: 99%

Velo and REXAN — Integrated data management and high speed analysis for experimental facilities

Dam

Carson

Corrigan

et al. 2012

2012 IEEE 8th International Conference on E-Science

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The Chemical Imaging Initiative at the Pacific Northwest National Laboratory (PNNL) is creating a 'Rapid Experimental Analysis' (REXAN) Framework, based on the concept of reusable component libraries. REXAN allows developers to quickly compose and customize high throughput analysis pipelines for a range of experiments, as well as supporting the creation of multi-modal analysis pipelines. In addition, PNNL has coupled REXAN with its collaborative data management and analysis environment Velo to create an easy to use data management and analysis environments for experimental facilities. This paper will discuss the benefits of Velo and REXAN in the context of three examples:• PNNL High Resolution Mass Spectrometry -reducing analysis times from hours to seconds, and enabling the analysis of much larger data samples (100KB to 40GB) at the same time. • ALS X-Ray Tomography -reducing analysis times of combined STXM and EM data collected at the ALS from weeks to minutes, decreasing manual work and increasing data volumes that can be analysed in a single step. •Multi-modal nano-scale analysis of STXM and TEM data -providing a semi automated process for particle detection. The creation of REXAN has significantly shortened the development time for these analysis pipelines. The integration of Velo and REXAN has significantly increased the scientific productivity of the instruments and their users by creating easy to use data management and analysis environments with greatly reduced analysis times and improved analysis capabilities.

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Section: B Framework -Workflow Architecture On Medicimentioning

confidence: 99%

Velo and REXAN — Integrated data management and high speed analysis for experimental facilities

Dam

Carson

Corrigan

et al. 2012

2012 IEEE 8th International Conference on E-Science

View full text Add to dashboard Cite

show abstract

“…At PNNL we have considerable experience in building first-of-akind scientific user environments for computational chemistry [13] and bioinformatics [15]. These widely used technologies are targeted specifically at the respective domain scientists, and exploit a variety of off-the-shelf (e.g.…”

Section: Related Workmentioning

confidence: 99%

Velo

Gorton

Sivaramakrishnan

Black

et al. 2011

Proceedings of the 4th International Workshop on Software Engineering for Computational Science and Engineering

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Modern scientific enterprises are inherently knowledge-intensive. In general, scientific studies in domains such as geosciences, climate, and biology require the acquisition and manipulation of large amounts of experimental and field data in order to create inputs for large-scale computational simulations. The results of these simulations must then be analyzed, leading to refinements of inputs and models and additional simulations. Further, these results must be managed and archived to provide justifications for regulatory decisions and publications that are based on these models. In this paper we introduce our Velo framework that is designed as a reusable, domain independent knowledge management infrastructure for modeling and simulation. Velo leverages, integrates, and extends open source collaborative and content management technologies to create a scalable and flexible core platform that can be tailored to specific scientific domains. We describe the architecture of Velo for managing and associating the various types of data that are used and created in modeling and simulation projects, as well as the framework for integrating domain-specific tools. To demonstrate a realization of Velo, we describe the Geologic Sequestration Software Suite (GS 3 ) that has been developed to support geologic sequestration modeling. This provides a concrete example of the inherent extensibility and utility of our approach.

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“…At the Pacific Northwest National Lab (PNNL), we have worked with many scientists in domains such as climatology, biology [3] and hydrology. These scientists rely on workflow applications to perform their science, and typically the orchestration of data and processing is performed by scripts assembled in an ad hoc manner over several years.…”

Section: Introductionmentioning

confidence: 99%

Kepler + MeDICi Service-Oriented Scientific Workflow Applications

Chase

Gorton

Sivaramakrishnan

et al. 2009

2009 Congress on Services - I

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Scientific applications are often structured as workflows that execute a series of interdependent, distributed software modules to analyze large data sets. The order of execution of the tasks in a workflow is commonly controlled by complex scripts, which over time become difficult to maintain and evolve. In this paper, we describe how we have integrated the Kepler scientific workflow platform with the MeDICi Integration Framework, which has been specifically designed to provide a standards-based, lightweight and flexible integration platform. The MeDICi technology provides a scalable, component-based architecture that efficiently handles integration with heterogeneous, distributed software systems. This paper describes the MeDICi Integration Framework and the mechanisms we used to integrate MeDICi components with Kepler workflow actors. We illustrate this solution with a workflow application for an atmospheric sciences application. The resulting solution promotes a strong separation of concerns, simplifying the Kepler workflow description and promoting the creation of a reusable collection of components available for other workflow applications in this domain.

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An Extensible, Scalable Architecture for Managing Bioinformatics Data and Analyses

Cited by 9 publications

References 24 publications

Velo and REXAN — Integrated data management and high speed analysis for experimental facilities

Velo and REXAN — Integrated data management and high speed analysis for experimental facilities

Velo

Kepler + MeDICi Service-Oriented Scientific Workflow Applications

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An Extensible, Scalable Architecture for Managing Bioinformatics Data and Analyses

Cited by 9 publications

References 24 publications

Velo and REXAN &#x2014; Integrated data management and high speed analysis for experimental facilities

Velo and REXAN &#x2014; Integrated data management and high speed analysis for experimental facilities

Velo

Kepler + MeDICi Service-Oriented Scientific Workflow Applications

Contact Info

Product

Resources

About

Velo and REXAN — Integrated data management and high speed analysis for experimental facilities

Velo and REXAN — Integrated data management and high speed analysis for experimental facilities