Welcome to the Laufer Center

Director

Physical principles of protein folding, statistical mechanics of water and aqueous solvation, computational models of protein-ligand interactions, and principles and biological applications of nonequilibrium statistical mechanics.

Associate Director
Carlos Simmerling (http://www.chem.stonybrook.edu/csimmerling.html)

Development of new algorithms and programs for accurate and efficient simulation of large biomolecular systems using state-of-the-art computers; development of tools for the visualization and analysis of the large amounts of data that are generated by our calculations.

Administrator

Junior Fellows
Christopher Fennell (http://www.dillgroup.ucsf.edu/~cfennell)
Justin MacCallum (http://www.dillgroup.ucsf.edu/~jlmaccal)

Postdoctoral Researchers
Alberto Perez
Daniel Farrell

Affiliated Faculty/Executive Committee

 Bruce Futcher (http://www.mgm.stonybrook.edu/futcher/index.shtml)

 Department of Molecular Genetics and Microbiology 

David Green (http://www.ams.sunysb.edu/~dfgreen/)

Current research in the Green Lab is focused on two primary biological systems: (1) signal transduction through the heterotrimeric G-protein pathway; and (2) the initial steps in the recognition of target cells by the HIV-1 virus. Each of these systems is being used to explore two distinct general problems of biological interest. The G-protein signal transduction pathway is our focus for explorations of the specificity of protein–protein interactions, while HIV–cell recognition is our prototypical system for understanding the role of glycosylation in modulating the interactions of proteins. In each system, sub-projects are focused on specific questions.

Sergei Maslov (http://www.cmth.bnl.gov/~maslov/)

My current research concentrates on topics in systems and computational biology with particular emphasis on properties of complex biomolecular networks.  In my studies I often (but not always) use the tools of theoretical statistical physics.  Even more important than tools, physics taught me the power of simple models in revealing the essence of complex phenomena. Simple models are indispensable if one wants not just to reproduce the complexity of a system (e.g. by a detailed computer simulations) but to truly understand it. 

Robert Rizzo (http://rizzo.ams.sunysb.edu/)

All-atom modeling of protein-ligand binding with emphasis on drug resistance, algorithm and protocol development to aid structure-based drug design and high throughput virtual screening (docking).

Steve Skiena (http://www.cs.sunysb.edu/~skiena/)

Combinatorial algorithm design and its applications to biology, particularly sequence analysis/assembly and gene design for synthetic biology.

Members

Jin Wang (http://www.chem.stonybrook.edu:82/Jin-Wang.html)

Physics and Chemistry of Biomolecules and Cellular Networks: One focus of my research is on the study of the fundamental mechanism of biomolecular folding and recognition, especially protein folding and protein-protein/protein-DNA interactions. Using modern statistical mechanics, molecular simulations and empirical information from protein database, energy landscapes of protein folding and recognition can be mapped. By further studying the detailed structure correlations of the landscape, the fundamental questions such as nucleations and nature of transition state ensemble can be answered for different proteins and biomolecular recognition complexes. The results of the study can be compared with the experiments. The energy landscape description of protein folding and recognition will also provide insight of new algorithms of structure prediction and drug design.

Another focus of my research is on the study of the underlying principles of the cellular networks. In particular, I am interested in the nature of the robustness of the cellular networks in the noisy fluctuating environments. I am also interested in understanding and quantifying the dynamics and pathways of the cellular networks. These studies should lead to optimal design and evolution of the networks. A general theoretical framework of landscape and flux is established to uncover the global nature of the non-equilibrium systems and networks from physical perspectives.

Michael Schatz (http://schatzlab.cshl.edu)

Michael Schatz is an assistant professor of computational biology in the Simons Center for Quantitative Biology at Cold Spring Harbor Laboratory, and an associate member of the Laufer Center for Physical and Quantitative Biology at Stony Brook University. His research interests include high performance computing and algorithms design towards large-scale sequence analysis problems in human and plant genetics. Schatz has 10 years of experience developing free and open source informatics tools for comparative genomics and genome assembly, which have been applied to genomes across the tree of life including: viruses and microbial genomes, human parasites, plants, fungi, insects, birds, and mammals. In recent years, Dr. Schatz has pioneered the use of cloud computing for DNA sequence analysis, by publishing the first ever and widely recognized algorithms CloudBurst and Crossbow for parallel short read mapping and SNP genotyping. Current projects include identifying de novo mutations associated with autism, structural variations in esophageal cancer, and improved methods for plant genome assembly using third generation sequencing technologies. Schatz received his Ph.D. and M.S. in Computer Science from the University of Maryland in 2010 and 2008, and his B.S. in Computer Science from Carnegie Mellon University in 2000.

Joshua Rest (http://life.bio.sunysb.edu/ee/restlab/index.htm)

For many genes, exactly when, how much, and where the gene is expressed is extremely important, and mistakes can lead to low fitness or disease. For these genes, any variation from these parameters has important selective consequences for the cell. For other genes, when, how much, and where the gene is expressed is not always important: this type of variation is neutral. In order to map out this fundamental architecture behind gene regulation and identify the evolutionary processes that are responsible, my research focus is to investigate the consequences of variation in gene regulation. We are measuring the extent that changes in the expression of genes result in changes in the fitness (reproductive capacity) of cells. We alter the expression level of a given gene using a repressible promoter, and measure the resulting fitness by competing the cells with altered expression against cells with normal expression. The focus of a second experimental project is on understanding the extent that this interference has shaped the expression patterns of genes by looking at pairs of genes that are naturally anti-correlated in their expression patterns. We artificially turn on these genes at the same time and location in the cell to see if there is a high fitness cost for expressing them at the same time. We are also investigating the contribution of variation in persistent versus transient responses to a cell's fitness. We predict that variation in transient gene transcription responses will be neutral if they are brief enough that protein levels are not affected, but that even very brief transcriptional responses will be meaningful if there is a resulting change in the amount of translated protein.

These experimental projects will create multi-dimensional map relating variation in a phenotype—gene regulation—to fitness, and therefore, natural selection and genotypic change. In doing so, these projects generate insights into the fundamental architecture of the cell and its variation through mutation.

F. William Studier (http://www.bnl.gov/biology/people/studier.asp)

Research has centered on conformations and interactions of DNA, molecular genetics and biochemistry of bacteriophage T7, and making T7 RNA polymerase and T7 expression signals useful for production of RNAs and proteins. A recent interest is comparative analysis of genome sequences of E. coli laboratory and commensal strains, and what they can reveal about bacterial evolution and the effects of laboratory manipulations.

Affiliated Departments
Applied Math (http://www.ams.sunysb.edu/)
Chemistry (http://www.chem.stonybrook.edu/)
Physics (http://www.physics.sunysb.edu/Physics/)
Computer Science (http://www.cs.sunysb.edu/)
Molecular Genetics and Microbiology (http://www.mgm.stonybrook.edu/index.shtml)

Upcoming Events

Yuhai Tu

Date: March 20, 2012

Title: TBA

Willy Wriggers

Date: April 24, 2012

Title: Emergent Complexity of Multiscale Computational Modeling

Past Events