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Leonid Mirny leonid[at]mit[dot]edu |
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Grigory Kolesov University of Munich, Ph.D. in Biology Evolution and prediction of specificity-determining residues
grigory[at]mit[dot]edu |
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Maxim Imakaev MIT Physics, Ph.D. Student mimakaev[at]gmail[dot]com |
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Jason Leith Harvard Biophysics, Ph.D. Student Several classes of proteins, including transcription factors, DNA-repair enzymes, and restriction enzymes, bind highly specifically to one or a few particular sites on a genome of millions to billions of base pairs. These proteins often are able to locate, using only thermal energy, and bind to their specific sites orders of magnitude faster than simple 3-D diffusion would allow. How they find their sites and recognize them so quickly, while avoiding "mislocalization", is not fully understood. Recent single-molecule experiments have verified predictions that these proteins would bind non-specifically to DNA and undergo 1-D diffusion in order to speed up the search process. Our lab has proposed that these sliding proteins undergo a conformational transition between a fast-sliding state and a stable-binding state, so that they can locate their cognate sites quickly and still bind securely. Very recent structural studies that have shown that the conformation of transcription factors and restriction enzymes indeed differs depending on whether the protein is bound to its cognate site or to a non-specific sequence. My work involves simulating the search, re-folding, and binding processes to better understand the physical parameters that govern the efficiency and stability of target binding. Additionally, I collaborate with Antoine van Oijen's group at Harvard Medical School in performing single-molecule microscopy experiments that examine the dynamics of p53's sliding on DNA. jleith[at]fas[dot]harvard[dot]edu |
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Alex Shpunt Ph.D. Student Various processes in biology depend on a combinatorial assembly of complex control molecules. What factors orchestrate this assembly and what makes it so fast and accurate? I am interested in stochastic processes in self-assembly of biological particles on a scaffold. In addition, I am working on analytical population genetics models, in collaboration with Harvard Medical School professor Shamil Sunyaev's group. There, we develop analytical methods to help predict genes that are connected to common diseases, designing and guiding future re-sequencing studies.
ashpunt[at]mit[dot]edu |
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Anahita Tafvizi Harvard Physics, Ph.D. Student I am working on two projects, both involving the interaction between transcription factors and DNA. The first is a bioinformatics project, in collaboration with Boris Reizi's lab at Columbia University, to determine whether Zfx and other eukaryotic transcription factors require clusters of binding sites rather than a single motif to perform their biological function. The second is a single-molecule microscopy project that aims to understand how tumor-suppressor p53 locates its promoter sites as rapidly as it does, which is critical for the proper carrying out of its function. Earlier bulk experiments have suggested that p53 diffuses in 1D along DNA. In collaboration with Antoine van Oijen's group at HMS, I have directly observed single molecules of p53 sliding on DNA. I am currently investigating the effects of salt concentration and truncations or mutations on p53's diffusive behavior, to better understand the physical basis for the protein's search process. atafvizi[at]fas[dot]harvard[dot]edu |
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Jonathan Friedman MIT Computational and Systems Biology Two-component signaling elements consiting of a histidine kinase and a response regulator are abundant in prokaryotes, and possess either a monofunctional or bifunctional mechanism. My project has two parts: 1) I am examining characteristics such as noise filtering and robustness of each mechanism using the total quasi steady-state approximation, in hopes of better understanding the ubiquity of these two mechanisms in prokaryotes and whether they are adapted to perform distinct tasks. 2) I am examining the steady-state behavior of systems that incorporate these mechanisms by considering the flux of phosphate. Previous work has shown that a bifunctional system can be robust to fluctuations in the concentration of signaling molecules, but that a monofunctional system cannot be. We have proposed, however, a modified monofunctional system that can indeed be robust to these fluctuations. 617.452.4075 |
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Maitagorri Schade MIT, B.A. Student maita[at]mit[dot]edu |
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Michael Schnall-Levin MIT Mathematics, Ph.D. Student Transcriptional Regulation: Factors Beyond Binding Motif Matches mschnall[at]gmail[dot]com |
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Ivan Adzhubey Moscow State University, Ph.D. in Biology Bioinformatics infrastructure development and maintenance |
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Vincent Bérubé, Ph.D. Student MIT Physics, Ph.D. Student Stochastic models of ion channels |
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Juhi Chandalia, Masters Student MIT, B.S., M.S. Structure and evolution of regulatory networks |
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Carlos Gómez-Uribe, Ph.D. Student HST MEMP/BIG, Ph.D. Stochastic models of signaling networks |
| Hao Yuan Kueh, Rotation Student Harvard Biophysics Princeton University, B.S. Information transmission in enzymatic switch |
| Joe Levine, Masters Student MIT, B.S., M.S. Dynamics of signaling cascades |
| Lewyn Li, Postdoctoral Fellow Columbia University Harvard University, Ph.D. in Chemistry Specificity determining residues in protein kinases |
| Shankar Mukherji, Undergraduate Student MIT, B.S. Dynamics of signaling cascades |
| Ilya Rudkevich, Undergraduate Student Brandeis University, B.S. Prediction of natively unstructured proteins |
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Michael Slutsky, Ph.D. Student MIT, Ph.D. in Physics Biophysics of protein-DNA interactions |
| Victor Spirin, Postdoctoral Fellow Boston University, Ph.D. in Physics Structure and regulation of biological networks |
| Zeba Wunderlich, Ph.D. Student Harvard University, Ph.D. in Biophysics Modeling of the transcription factor search process Energetics of protein-protein interactions |