August 2006
Trends and Tools in Bioinformatics and Computational Biology
Wilfred W. Li, University of California, San Diego (UCSD), San Diego Supercomputer Center (SDSC)
Nathan Baker, Washington University in Saint Louis
Kim Baldridge, UCSD, SDSC
J. Andrew McCammon, UCSD
Mark H. Ellisman, UCSD, Center for Research In Biological Systems (CRBS)
Amarnath Gupta, UCSD, SDSC
Michael Holst, UCSD
Andrew D. McCulloch, UCSD
Anushka Michailova, UCSD
Phil Papadopoulos, UCSD, SDSC
Art Olson, The Scripps Research Institute (TSRI)
Michel Sanner, TSRI
Peter W. Arzberger, California Institute for Telecommunications and Information Technology (Calit2), CRBS, UCSD

3. Computational and data cyberinfrastructure to support multiscale modeling

In parallel to efforts focusing attention on the needs and the benefits of multiscale modeling, tremendous national and international investments have already been made to develop and deploy a cyberinfrastructure that will revolutionize the conduct of science.34 This cyberinfrastructure consists of distributed computational, data storage, observational, and visualization resources, including human resources, connected by a network infrastructure and a software layer (middleware), that will “bring access of resources (at one end) to researchers (at another) and allow researchers to conduct team science as part of normal conduct of science 35, in an end-to-end cyberinfrastructure.” Cyberinfrastructure, and grid, are often used interchangeably.36

The necessary grid infrastructure to support the multiscale modeling community remains to be defined through an iterative process with ongoing interactions between scientists and infrastructure developers. There has been significant progress in the development of the networks and physical resources that are the fabric of the grid.37 However, the middleware layer, which connects the fabric with the users and applications, is still in a state of flux. To increase the usability and decrease the cost of entry of the grid, new programming models or application execution environments are being developed, and sometimes these are referred to as grid application-level tools.38 These tools are designed to be built on top of the grid software infrastructure. They are generic, easy to use and shield the users from changes in underlying architecture.

An “end-to-end” cyberinfrastructure for multiscale modeling needs to have the capability to handle the representative data commonly encountered in MSM, by representative users who need to accomplish tasks that are representative of the nature of MSM research and development. The scientific drivers for multiscale modeling at NBCR are diverse and span the scale from subatomic electron charge density flows in development of better photodynamic therapies 39, to cellular and whole heart physiology modeling,1 with information integration technology providing the mediator necessary for interoperability. All these projects drive the development and integration effort we are leading to provide the cyberinfrastructure necessary and required for the research objectives to be met. In addition, NBCR works closely with other projects at UCSD, such as NCMIR, BIRN,40 CAMERA,41 Optiputer,42 JCSG,43 and establishes important collaborations with national projects such as TeraGrid,44 Open Science Grid,45 as well as international projects such as PRAGMA46 and OMII.47

Figure 5

Figure 5. Selected Components of NBCR Software Service Stack. Colored blocks and arrows indicate possible routes for distributed job execution. The different green shades show possible routes to access physical computational resources, and the arrows.

The development of infrastructure that can support diverse applications using distributed physical resources and remain easy to use and scalable has ushered in the service-oriented architecture as the dominant modus operandi for reasons eloquently stated in.48 To enable scientific applications on the grid, many different approaches have been adopted.49 We have taken a minimalist approach, which is to select the most stable components, achieve the greatest leverage, and develop smart glues that are reusable components, within the service oriented approach (Figure 5). We’ll highlight some key components developed by or with critical contributions from NBCR and then discuss how they are used to support multiscale modeling efforts at NBCR and how they are available to the MSM community in general.

Upper middleware services are those that make the development of distributed applications significantly easier, with support for higher levels of abstraction and standardization. For example, NBCR Opal based application web services provide job management and scheduling features based on the Globus toolkit. An application developer may begin using the grid quickly with the basic knowledge of web service development, as shown by the use cases in PMV, My WorkSphere, and Gemstone user environments. Lower middleware services are those that have stabilized over the years and serve as the foundation for the development of more sophisticated and transparent modes of access. However, as often dictated by performance requirements, a user application may access lower layers directly. This is much less desirable unless the integration is based on the service oriented architecture. Below we describe some key tools and technology actively developed or co-developed by NBCR to support our user communities. For a more comprehensive description of all the tools and software, please see NBCR download site.50

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Reference this article
Li, W. W., Baker, N., Baldridge, K., McCammon, J. A., Ellisman, M. H., Gupta, A., Holst, M., McCulloch, A. D., Michailova, A., Papadopoulos, P., Olson, A., Sanner, M., Arzberger P. W. "National Biomedical Computation Resource (NBCR): Developing End-to-End Cyberinfrastructure for Multiscale Modeling in Biomedical Research," CTWatch Quarterly, Volume 2, Number 3, August 2006. http://www.ctwatch.org/quarterly/articles/2006/08/national-biomedical-computation-resource/

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