Active grants are from the
National Science Foundation
(NSF) and the National Institutes of Health (NIH):
- NSF-ITR-EIA-0325550
9/15/03 - 8/31/06
Subnanometer Structure Based Fold Determination of Biological Complexes
An interdisciplinary collaboration with Prof.
Wah Chiu
of Baylor College of Medicine, and Prof.
Andrej Sali of
University of California, San Francisco,
to develop computational and visualization tools for feature extraction
and structure modeling of large macromolecular complexes based on sequence data
and in conjunction with subnanometer resolution cryo-Electron Microscopy (cryo-EM).
- NIH-R01 GM074258-02
4/1/05 - 3/31/08
Hierarchical Methods for Large Biomolecular Complexes
To develop and implement efficient algorithms for determining structural features
of macromolecules from 3D-EM (Electron Microscopy) maps at multiple resolutions,
and for generating hierarchical, volumetric spline approximations
of the determined structural features to facilitate
fast Fourier based matching of geometry and imaging.
- NIH-R01 GM073087-01
03/01/06 - 02/28/09
A New Approach to Rapid Protein-Protein Docking
The principal aims are to develop, implement and test novel m
athematical algorithms that speed up computational protein-protein docking espec
ially for larger problems, as well as to significantly improve the prediction of
protein-protein binding. This collaborative project also has a subcontract to D
r. Art Olson and Dr. Michel Sanner at The Scripps Research Institute, San Diego,
CA for testing and validation.
- NSF-ITR-ACI-0220037
10/1/02 - 1/30/06
Large Scale Simulations of Emulsions
An interdisciplinary collaboration with Prof.
Gregory J. Rodin
of Mechanical Engineering
and Prof. Roger Bonnecaze
of Chemical Engineering,
and is concerned with large-scale micromechanical simulations,
analysis and visualization of low-Reynolds-number or Stokesian emulsions.
- NIH-P20 RR020647-01
10/1/04 - 9/31/07
Towards a Computational Center for Biomolecular Complexes
A multi-institutional planning grant,
Computational Center for Biomolecular Complexes
(C2BC), linking
the National Center for Macromolecular Imaging,
Baylor College of Medicine
(Dr. Wah Chiu),
the PDB and Structural Biology research, Rutgers University
(Dr. Helen Berman),
and the Molecular Graphics Laboratory,
The Scripps Research Institute
(Dr. Art Olson),
is to develop a virtual center spanning the four institutions to foster computational techniques
and tools for large macromolecular structural biology.
- NSF-EIA-0303609
9/1/03 - 8-31-07
Mastadon:
A Large-Memory, High-Throughput Simulation Infrastructure
Computer Sciences
department's hardware infrastructure development grant
for computations requiring massive data throughput.
- NSF-DDDAS-0540063
Dynamic Data-Driven System for Laser Treatment of Cancer
An interdisciplinary collaboration with
Prof. J.T.Oden of
The Institute for Computational Engineering and Sciences
Prof. C.Bajaj of
The Institute for Computational Engineering and Sciences,
Computer Sciences
Prof. J.C.Browne of
Computer Sciences ,
Prof. K.R.Diller of
Biomedical Engineering ,
Prof. I.Babuška of
The Institute for Computational Engineering and Sciences,
Dr. J.M.BASS of
The Institute for Computational Engineering and Sciences,
Prof. L. Demkowicz of
The Institute for Computational Engineering and Sciences
Dr. S.Prudhomme of
The Institute for Computational Engineering and Sciences
Dr. J.Hazle, MD of
The University of Texas MD Anderson Cancer Center
Dr. L.Bidaut, MD of
The University of Texas MD Anderson Cancer Center
and Dr. R.J.Stafford, MD of
The University of Texas MD Anderson Cancer Center,
to develop a dynamic data-driven planning, control, and visualization system for laser treatment of cancer. The proposed research
includes development of a general mathematical framework and a family of mathematical framework and a family of
mathematical and computational models of hio-heat transfer, tissue damage, and tumor viability, dynamic
calibration, verification and validation processes based protocols using model predictions. At the core of the
proposed systems is the adaptive-feedback control of mathematical and computational models based on a
poseriori estimates of errors in key quantities of interest, and mordern Magnetic Resonance Temperature
Imaging (MRTI) and diode laser devices to monitor treatment of tumors in laboratory animals.
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