Science In Silico: How Desktop Supercomputing Is Revolutionizing Science

Science In Silico
Reported by
Catherine Zandonella

Posted July 02, 2007


On February 16, 2007, the Academy's Frontiers of Science and Science Alliance programs collaborated to organize a special symposium for students and postdocs at the University of Miami. Researchers from a wide range of scientific disciplines—including computer science, protein folding, DNA folding, tornado prediction, and systems biology—spoke to students and postdocs about how vastly improved computational power is changing the way science is done.

Ralph Cavin of Semiconductor Research Corporation described new technologies that will enhance computer processing over the next 15 years and beyond. Harold Scheraga of Cornell University spoke about novel approaches to modeling protein folding. Tamar Schlick of the Department of Chemistry and Courant Institute of Mathematical Sciences at New York University discussed her work on dynamics simulations of DNA/chromatin folding. Sai Ravela of the Massachusetts Institute of Technology explained how to model hurricanes using laptop computers. And John Jeremy Rice of IBM described the promises and pitfalls of the systems approach to biology.

Use the tabs above to find a meeting report and multimedia from this event.

Web Sites

2020 Computing Technologies: A Fundamental Physics Perspective

SRC (Semiconductor Research Corporation)
An industry-sponsored research consortium that aims to solve technical challenges facing the semiconductor development through support of basic and applied university research and the training of new scientists.

Simulations of Protein Folding Pathways with Molecular Dynamics

World Wide Protein Data Bank
A central location for the deposition, processing, and distribution of macromolecular structural data that is freely and publicly available to the global community.

A distributed-computing project that uses personal computers connected via the Internet to simulate the folding of proteins.

Academic groups that study protein folding
These laboratory Web sites have information about many different kinds of protein folding projects.

7th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction
A multidisciplinary competition where research groups try to predict protein structure given an amino acid sequence.

Back to the Future of Systems Biology

Blue Brain
A collaboration between IBM and EPFL to create a biologically accurate, functional model of the brain using IBM's Blue Gene supercomputer.

DREAM Project
This project seeks to explore the ability to reverse engineer biological systems by presenting an opportunity to compare the strengths and weaknesses of algorithms and methods.


2020 Computing Technologies: A Fundamental Physics Perspective

Zhirnov VV, Cavin RK. 2006. Molecular electronics: chemistry of molecules or physics of contacts? Nat. Mater. 5: 11-12.

Simulations of Protein Folding Pathways with Molecular Dynamics

Khalili M, Liwo A, Jagielska A, Scheraga HA. 2005. Molecular dynamics with the united-residue model of polypeptide chains. II. Langevin and Berendsen-bath dynamics and tests on model alpha-helical systems. J. Phys. Chem. B 109: 13798-13810.

Khalili M, Liwo A, Rakowski F, et al. 2005. Molecular dynamics with the united-residue model of polypeptide chains. I. Lagrange equations of motion and tests of numerical stability in the microcanonical mode. J. Phys. Chem. B 109: 13785-13797.

Khalili M, Liwo A, Scheraga HA. 2006. Kinetic studies of folding of the B-domain of staphylococcal protein A with molecular dynamics and a united-residue (UNRES) model of polypeptide chains. J. Mol. Biol. 355: 536-547.

Liwo A, Khalili M, Scheraga HA. 2005. Ab initio simulations of protein-folding pathways by molecular dynamics with the united-residue model of polypeptide chains. Proc. Natl. Acad. Sci. USA 102: 2362-2367. Full Text

Computer Simulations on the "DNA Folding Problem"

Arya G, Schlick T. 2006. Role of histone tails in chromatin folding revealed by a mesoscopic oligonucleosome model. Proc. Natl. Acad. Sci. USA 103: 16236-16241. Full Text

Arya G, Zhang Q, Schlick T. 2006. Flexible histone tails in a new mesoscopic oligonucleosome model. Biophys. J. 91: 133-150.

Beard DA, Schlick T. 2001. Computational modeling predicts the structure and dynamics of chromatin fiber. Structure 9: 105-114. Full Text

Beard DA, Schlick T. 2001. Modeling salt-mediated electrostatics of macromolecules: the discrete surface charge optimization algorithm and its application to the nucleosome. Biopolymers 58: 106-115.

Bednar J, Horowitz RA, Grigoryev SA, et al. 1998. Nucleosomes, linker DNA, and linker histone form a unique structural motif that directs the higher-order folding and compaction of chromatin. Proc. Natl. Acad. Sci. USA 95: 14173-14178. Full Text

Schlick T. 2003. Engineering teams up with computer-simulation and visualization tools to probe biomolecular mechanisms. Biophys. J. 85: 1–4. Full Text

Strahs D, Schlick T. 2000. A-Tract bending: insights into experimental structures by computational models. J. Mol. Bio. 301: 643-663.

Sun J, Zhang Q, Schlick T. 2005. Electrostatic mechanism of nucleosomal array folding revealed by computer simulation. Proc. Natl. Acad. Sci. USA 102: 8180-8185. Full Text

Wang Y, Reddy S, Beard WA, et al. 2007. Differing conformational pathways before and after chemistry for insertion of dATP versus dCTP opposite 8-OxoG in DNA polymerase {beta}. Biophys. J. 92: 3063-3070.

Models for Inference in the Ocean and Atmosphere

Emanuel K, Ravela S, Risi C, Vivant E. 2006. A statistical deterministic approach to hurricane risk assessment. Bulletin of American Meteorological Society (March)

Ravela S, Emanuel K, McLaughlin D. (in press) Data assimilation by field alignment. Physica (D)

Back to the Future of Systems Biology

Hu W, Feng Z, Ma L, et al. 2007. A single nucleotide polymorphism in the MDM2 gene disrupts the oscillation of p53 and MDM2 levels in cells. Cancer Res. 67: 2757-2765.

Kozloski J, Hamzei-Sichani F, Yuste R. 2001. Stereotyped position of local synaptic targets in neocortex. Science 293: 868-872.

Lepre J, Rice JJ, Tu Y, Stolovitzky G. 2004. Genes@Work: an efficient algorithm for pattern discovery and multivariate feature selection in gene expression data. Bioinformatics 20: 1033-1044. (PDF, 620 KB) Full Text

Rice JJ, Tu Y, Stolovitzky G. 2005. Reconstructing biological networks using conditional correlation analysis. Bioinformatics 21: 765-773. Full Text


Ralph K. Cavin, III, PhD

Semiconductor Research Corporation

Ralph Cavin is vice president for Research Operations at Semiconductor Research Corporation. Cavin's technical interests span VLSI circuit design, computer-aided design of microelectronic systems, control theory with applications to semiconductor manufacturing, and applications of computing and telecommunications to engineering education.

Cavin received his PhD in Electrical Engineering from Auburn University in 1968. After taking his PhD, Cavin joined the faculty of the Department of Electrical Engineering at Texas A&M University where he obtained the rank of full professor and also served the department as assistant head for research. In 1983 he joined the Semiconductor Research Corporation where he served as director of design sciences research programs until 1989. He became head of the Department of Electrical and Computer Engineering at North Carolina State University from 1989 to 1994 and was dean of Engineering from 1994 to 1995.

Cavin is a fellow of the Institute for Electrical and Electronics Engineers (IEEE). He has served as a consultant to a number of government, industrial, and academic institutions and is a member of the Board of Directors of the International Engineering Consortium and the IEEE Computer Advisory Board.

Harold A. Scheraga, PhD

Cornell University
e-mail | web site | publications

Harold Scheraga is the George W. and Grace L. Todd Professor of Chemistry, Emeritus at the Baker Laboratory of Chemistry and Chemical Biology at Cornell University. His laboratory is investigating the interactions that dictate the folding of a polypeptide chain in water into the three-dimensional structure of a native protein and that determine the reactivity of such a protein molecule (e.g., as an enzyme) with other small and large molecules.

Scheraga has won numerous honors and awards. He was a Guggenheim Fellow and a Fulbright Research Scholar. He is an elected member of the National Academy of Sciences and the American Academy of Arts and Sciences. He is also an honorary life member of the New York Academy of Sciences. Scheraga has won the ACS Mobil Award in Polymer Chemistry, the ACS Repligen Award for Chemistry of Biological Processes, and many others.

Scheraga obtained his PhD from Duke University.

Tamar Schlick, PhD

Courant Institute of Mathematical Sciences
New York University
e-mail | web site | publications

Tamar Schlick is professor of chemistry, mathematics, and computer sciences in the Department of Chemistry and the Courant Institute of Mathematical Sciences. She was the director of the new multidepartmental Computational Biology Doctoral Program at the Graduate School of Arts and Sciences and director of program development for the Department of Chemistry at NYU from 2003 to 2006. Schlick was an associate investigator of the Howard Hughes Medical Institute from 1994 to 2003. Schlick has received many honors, including being named 2005 Businesswoman of the Year, an American Physical Society Fellow, and an American Association for the Advancement of Science Fellow.

Tamar Schlick obtained her MS and PhD in applied mathematics at the Courant Institute of Mathematical Sciences at New York University.

Sai Ravela, PhD

Massachusetts Institute of Technology
e-mail | web site | publications

Sai Ravela is a research scientist in Computational Earth Science at Massachusetts Institute of Technology. He studied computer vision and robotics at the University of Massachusetts at Amherst and received his PhD in 2002.

His enduring research interest is to design and use methods that can answer queries about the behavior of stochastic spatio-temporal processes. To do so, he studies estimation, control, decision, and information theories. Currently, he focuses on earth systems estimation, specifically to design algorithms that overcome the problems of nonlinearity, dimensionality and uncertainty that is characteristic of earth problems and a real barrier to effective predictability.

J. Jeremy Rice, PhD

IBM T.J. Watson Research Center
e-mail | web site | publications

John Jeremy Rice is a research staff member of the Functional Genomics and Systems Biology Group at IBM's T. J. Watson Research Center. He is also an adjunct faculty member in the Department of Engineering at the Johns Hopkins University. Rice obtained his PhD from the Department of Biomedical Engineering at Johns Hopkins University. Prior to joining IBM Research, Rice was a computational modeler and research scientist at Physiome Sciences in Princeton, New Jersey.

Catherine Zandonella

Catherine Zandonella is a science writer based in New York City, covering such topics as environmental science, public health, and applied technology. She has a master's degree in public health from the University of California, Berkeley. Zandonella has written for a number of publications, including New Scientist, The Scientist, and Nature.