Abstract
Challenges in Creating an Infrastructure for Physics-Based Simulation of Biological Structures
Physics-based simulation provides a powerful framework for understanding biological form and function. Physical simulations
may be used by biologists to study macromolecular assemblies and by clinicians to examine disease mechanisms. Simulations
help biomedical researchers understand the physical constraints on biological systems as they engineer novel drugs, drug
delivery systems, synthetic tissues, medical devices, and surgical interventions. Although individual investigators have
made elegant contributions to physics-based modeling in biomedicine, the field is fragmented. Modeling applications are
typically limited to a single physical scale, and individual investigators frequently must create their own software. These
conditions create a major barrier to advancing simulation capabilities, and its general availability to biomedical researchers
working on problems critical to health. We have established a National Center for Physics-Based Simulation of Biological
Structures (Simbios, http://simbios.stanford.edu/) to help integrate the field and accelerate future research.
Simbios is developing, disseminating, and supporting a simulation tool kit, SimTK, (http://www.simtk.org/) that will enable
biomedical scientists to develop and share accurate models and simulations of biological structures from molecules to organisms.
The challenges to this effort include (1) the creation of an open-source, extensible, object-oriented framework for manipulating
data, models, and simulations, (2) encouraging a culture of sharing among scientists who develop innovative methods for physics-based
simulation, (3) balancing the needs of biomedical researchers who want end-to-end applications, with tool builders who want access
only to key algorithms, and (4) ensuring that our models, methods, and applications are disseminated and applied to important
problems in biomedicine, thus accelerating progress in understanding and fighting disease.
In order to guarantee that real biomedical problems inform the creation of SimTK, the first set of driving biological problems
for Simbios have been selected across physical scales and include RNA folding & dynamics, myosin dynamics, biomechanics, and
cardiovascular fluid dynamics. The software we create is built by teams working to innovate and push the frontiers of science
in these four areas, but will be applicable to a much wider range of application areas. We have an active set of additional
collaborations to ensure generality
Biography
Education
AB Harvard College, 1983 - Biochemistry & Molecular Biology
PhD Stanford University, 1989 - Medical Information Science
MD Stanford University, 1990 - Medicine
Research
I am interested in the application of computational technologies to problems in molecular biology of relevance
to medicine. In particular, my laboratory focuses on three areas. First, we are interested in building structured
information repositories to support biological research. Our first effort was the RiboWEB resource for supporting
studies of the bacterial ribosome (http://riboweb.stanford.edu). Our latest effort is in the creation of a
comprehensive pharmacogenomics knowledge base that provides access to information relating genotype to phenotype
(in particular, how variation in genetics leads to variation in response to drugs). Second, we are interested in
the elucidation and analysis of three dimensional structures. We have projects for computing 3D molecular structures
from sparse and noisy data, and for analyzing these structures to recognize and annotate active sites. We are interested
in physics-based simulation of biological structures. Third, we are interested in computational methods for analyzing
functional genomics information. We are focusing on the use of natural language processing techniques for extracting
and summarizing information, and in the development of novel methods for analyzing microarray expression data. We are
applying these technologies to the study of functional genomics.
Contact:
Department of Genetics
Stanford University Medical Center
300 Pasteur Drive, Lane 301, Mail Code: 5120
Stanford, CA 94305-5120
(650) 725-3394
russ.altman@stanford.edu
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