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Projects |
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The key
aim of this resource is to provide transparent access
to the new and emerging grid infrastructure that
will deliver integrated compute, data, physical, experimental,
and human resources to biomedical scientists investigating a
wide range of medically important problems spanning scales of
biological organization from small molecule drug design and
comparative genomics to diagnostic brain imaging and
cardiovascular disease. |
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Within this context, we are developing three key technologies: |
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Key technologies |
Cluster and grid computing: includes an integrated version of existing and emerging
technologies created in our other projects; will also include
specific software components and services; will enable
effective scheduling of three classes, ranging from
computationally intensive applications to simple, scheduled
update computations, to impulse or on-demand computing. |
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Data
and web services:
includes data modeling, data access—including
wrapping of information sources and use of XML-based
standards, and data integration across multiple
sources. |
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Visualization and interfaces:
includes the developing and hardening of visual,
component-based, interactive environments for biomedical
programming; computation, analysis and visualization that
will facilitate the rapid development, reconfiguration and
the novel utilization of multi-disciplinary and multi-scale
applications for biological research. In addition, this
technology will interoperate with those of the computing and
web services by providing a user-based front end to the grid
services used by the biomedical community. |
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These
technologies will be developed in the context of several
pressing biological needs from important applications at
various ranges of scales (e.g., atomic to macromolecular,
molecular to cellular, tissue to organ). This approach will
deliver concrete products used by specific communities as well
as ensure a more robust, scalable (i.e., not single
application) product. |
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The
projects,
with their high-level goals, include the following cores: |
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Core Projects |
1. Integrative Modeling of Subcellular
Processes: Application to Synaptic Activity and Pharmaceutical
Discovery: J. Andrew McCammon, Kim Baldridge,
Michael Holst, Nathan Baker, Philip Papadopoulos, Michel
Sanner: Develop computational approaches for simulating
multi-scale, subcellular processes with constitutive
descriptions derived directly from microscopic analyses such
as molecular simulations and ab initio calculations.
Numerical approaches are implemented into software packages
that are grid-enabled, verified on scientifically relevant
biomedical problems, and distributed via grid portals to
enhance biomedical research and development of potentially
viable pharmaceuticals and treatment protocols. |
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2. Data Integration and Analytic Tools for
Molecular Sequences: Amarnath Gupta, Kim Baldridge, Mary Ann Martone:
Integrate data resources and provide analytic tools in order
to create data laboratories in which the intersection of the
individual components produce tools that are more powerful
than the sum of their parts. Provide grid-enabled tools and
services with visual interfaces for delivering electronic data
analysis; searching, linking and joining electronic resources
for the biomedical community. |
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3. Structurally and Functionally Integrated
Modeling of Cell and Organ Biophysics:
Andrew McCulloch, Anushka Michailova, Mark Ellisman,
Michel Sanner, Philip Papadopoulos: Develop and deploy
novel, cluster-enabled, grid-aware software and data resources
that allow investigators in biomechanics, biophysics and
cardiovascular physiology to perform numerical experiments
that are: structurally integrated from sub-cellular to whole
organ scales; functionally integrated across interacting
biological processes; and that integrate experimental data
from a variety of sources, scales and modalities. |
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4. Creating Visualization Environments for
Multi-Scale Biomedical Modeling: Michel
Sanner, Arthur Olson: Provide the biomedical
community with powerful and flexible visual tools that will
facilitate the rapid development, reconfiguration and novel
utilization of multi-disciplinary and multi-scale applications
for biomedical research, by extending, hardening, and
deploying visual, component-based, interactive environments
for biomedical programming, computation, analysis and
visualization. Challenging biomedical problems under
investigation across the core projects of this resource and
several collaborative projects will drive the development of
these tools. The resulting applications and underlying
components will be made available to the broader biomedical
community via the grid environment. |
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5. Grid Computing and Analysis for Multi-scale
Biomedical Applications:
Peter Arzberger, Mark Ellisman, Kim Baldridge, Philip
Papadopoulos, Michel Sanner, Wilfred Li: Provide transparent access
to the emerging grid-based computational infrastructure
(cyberinfrastructure) by "grid-enabling" biomedical codes and
providing access to distributed biological and biomedical
databases. This will allow biomedical researchers to harness
the computational power and securely access very large data
resources and specialized instruments available in the
emerging and distributed grid environment. Our focus on key
biomedical applications will create new approaches to
provisioning resources on the grid; develop distributed
large-data integrative environments; develop approaches for
on-demand computing; "wrap" tools to create workflows for the
biomedical sciences by grid-enabling specific application
examplars; and establish and maintain a prototypical grid
resource for biomedical applications. |
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All
collaborative projects described relate to these collaborating
investigators' peer-reviewed and currently funded research
projects. |
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Collaborative projects are for
activities where some aspect of the proposed collaborative
research problem or experimental system makes it an
appropriate test bed for expanding application of the Resource
key technologies: transparent access to emerging grid
infrastructure, which collectively involves cluster and grid
computing, data and web services, and visualization and
interfaces. In most cases the collaborative project depends
heavily on a key technology but the emphasis in many is in
expanding application of resource technologies to projects of
biomedical relevance. In addition, we have chosen these
projects for their multiscale modeling components and their
potential for translational impact. |
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Collaborative Projects |
Modeling Flexibility and
Dynamical Motion in Complex Protein Systems. Principal
Investigator: F. Romesberg, Ph.D., The Scripps Research
Institute. Co-investigator: Kim Baldridge,
Ph.D. |
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New Antitumor Drugs.
Principal Investigators: Trevor McMorris, Ph.D.;
Co-investigator: Kim Baldridge, Ph.D. |
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Modeling the Structure and
Dynamics of Acetylcholinesterase Clusters, and Their Effects
on Acetylcholine Hydrolysis.
Principal Investigators: Palmer
Taylor, Ph.D, UC, San Diego.
Co-investigator: Andrew McCammon, Ph.D. |
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Modeling Energy Transfer
Processes in Biological Probe Molecules.
Principal Investigator: P.
Selvin, Ph.D., University of Illinois at Urbana-Champaign |
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Integrative Cardiac Myocyte
Model: Ion Channels, Ca and Contraction. Principal
Investigator: Don Bers, Ph.D., Loyola of Chicago |
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The Role of Anatomic Structures
in Ventricular Fibrillation. Principal Investigators: Alan
Garfinkel, Ph.D., UCLA; ; Co-investigator: James Weiss, Ph.D.,
UCLA |
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Mechanoelectric Feedback in
Cardiac Defibrillation.
Principal Investigators:
Natalia Trayanova, Ph.D., Tulane |
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Visualization Tools for
Automated Molecular Microscopy.
Principal Investigators:
Bridget Carragher, Ph.D., Clinton Potter, The Scripps Research
Institute |
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Scientific Animation Tools for
Biomedical Applications.
Principal Investigator: Wah Chu,
Ph.D., Baylor College of Medicine |
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"Click Chemistry" Assembly of
HIV Protease Inhibitors. Principal Investigators: Barry
Sharpless, Ph.D., The Scripps Research Institute;
Co-investigator: M.G. Finn, Ph.D., The Scripps Research
Institute |
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Novel Anti-Cancer Drug Design
Targeting AICAR Transformylase in the Purine de novo
Biosynthetic Pathway.
Principal Investigators: Ian
Wilson, Ph.D., The Scripps Research Institute;
Co-investigator: Dale Boger, Ph.D., The Scripps Research
Institute |
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Protein Data Bank Grid Service. Principal
Investigators: John Westbrook, Ph.D., Rutgers University;
Co-investigator: Helen Berman, Ph.D., Rutgers University |
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Grid Services in the Genomic
Analysis: Connectivity Maps and Molecular Pattern Recognition. Principal
Investigator: Jill Mesirov, Ph.D., Whitehead Institute, MIT;
Co-investigators: Eric Lander, Ph.D., Whitehead Institute,
Pablo Tamayo, Ph.D., Whitehead Institute |
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Enhanced Access to
Data-intensive, High Throughput Output of Structural Genomics.
Principal Investigators: Ian Wilson, Ph.D., The Scripps
Research Institute; Co-investigator: Adam Godzik, Ph.D.,
Burnham Institute and UCSD; Associates: Peter Kuhn, Ph.D., The
Scripps Research Institute, John Wooley, Ph.D., UCSD |
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Service Projects offer a
way to demonstrate explicitly the broadening impact of this
Resource. |
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There are many mechanisms through which NBCR will
provide service to the biomedical community. Specific service
mechanisms include: Web-based access to service, Software
downloads, Interactions with users and other centers,
including Key User Program (KUP) |
| For selected service projects, please visit the User Services.
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