Gregory R. Bowman

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bowman_face Miller Research Fellow
260L Stanley Hall #3220
University of California
Berkeley, CA 94720-3220
gregoryrbowman (at) gmail [dot] com

Software

MSMBuilder

Markov state models (MSMs) are a powerful means of mapping out the conformational space of biomolecules, allowing one to model both their thermodynamics and kinetics. The MSMBuilder project I started in collaboration with Xuhui Huang and Vijay Pande automates the construction of MSMs from molecular simulations.  A number of developers are now contributing to the project.

BACE

The Bayesian agglomerative clustering engine (BACE) is a method for coarse-graining Markov state models (MSMs) in a manner that takes into account model uncertainty. Code is available here.

CV

A pdf version of my CV can be downloaded here.

Education

2006-2010 Ph.D. in Biophysics, Stanford University, Stanford, CA (adviser Vijay Pande)

2002-2006 BS summa cum laude in Computer Science with a minor in Biomedical Engineering, Cornell University, College of Engineering, Ithaca, NY (advisers Roger Loring and Graeme Bailey)

1998-2002 Thomas Jefferson High School for Science and Technology, Alexandria, VA

Academic Research Experience

Miller Research Fellow with Susan Marqusee and Phillip Geissler, Department of Molecular & Cellular Biology and Department of Chemistry, University of California, Berkeley, 2011-present

  • Developed and applied methods for understanding and predicting protein functional dynamics—like allostery. Began learning experimental techniques for testing my predictions from theory and simulation.

Berry postdoctoral fellow with Vijay Pande, Department of Chemistry, Stanford University, 2010-2011

  • Developed and applied methods for modeling protein folding (70-80 residue proteins, millisecond folding times) and misfolding. Began independent work on protein-ligand and protein-protein interactions.

Ph.D. with Vijay Pande, Biophysics Program, Stanford University, 2006-2010

  • Developed and applied methods for modeling protein folding dynamics (30-40 residue proteins, microsecond folding times).

Undergraduate Research with Roger Loring, Department of Chemistry, Cornell University, 2005-2006

  • Calculation of vibrational echo spectroscopy from simulations of carbonmonoxy myoglobin.

Undergraduate Research with Graeme Bailey, Department of Computer Science, Cornell University, 2003

  • Created screen magnification software for the Linux operating system to make Linux accessible to the visually impaired.

Professional Experience

iPhone Application Development, Self-employed, 2011-present

Software Development, Gene Network Sciences, Ithaca, NY, 2006

  • Led a team of five students to develop software for representing gene networks.

Summer Intern, U.S. Naval Medical Research Institute, Rockville, MD, 2004

  • Developed a toolkit to design gene resequencing microarrays.

Summer Intern, Cubic Corporation, Alexandria, VA, 2002 and 2003

  • Developed software for the construction of 3-dimensional models of buildings from their blueprints.

Honors and Awards

Burroughs Wellcome Fund Career Award at the Scientific Interface ($500k transition award that will follow me to a faculty position), 2013-2018

Miller Research Fellowship, University of California, Berkeley, 2011-2014

Young Investigator Award, Genome Technology, 2011

Berry Postdoctoral Fellowship, Stanford University, 2010-2011

Thomas Kuhn Paradigm Shift Award, American Chemical Society, 2010

National Science Foundation Graduate Research Fellowship, 2007-2010

Tau Beta Pi, Cornell University, 2006

Merrill Presidential Scholar, Cornell University, 2006

Computer Science Department Award for Academic Excellence, Cornell University, 2006

Rhodes Scholarship Finalist, 2005

Jean Dreyfus Boissevain Undergraduate Scholarship for Excellence in Chemistry, Cornell University, 2005

Invited Talks

Biophysics Seminar, University of Michigan, 2013

Physical Chemistry Seminar, University of California, Berkeley, 2013

Physical Chemistry Seminar, University of Pennsylvania, 2013

Physical Chemistry Seminar, ETH Zurich, 2012

Biophysics Seminar, University of California, San Francisco, 2012

Biophysics Seminar, Johns Hopkins University, 2012

Protein Folding Workshop, Stony Brook, 2012

Folding@home conference, Stanford University, 2012

Protein Folding Workshop, University of California, Berkeley, 2011

RosettaCon, University of Washington, Seattle, 2011

Protein Folding Symposium, Hong Kong University of Science and Technology, 2011

Thomas Kuhn Paradigm Shift Award Symposium, American Chemical Society, 2010

Protein Folding & Stability Platform Session, Biophysical Society, 2010

France-Stanford Exchange Program, Institut Pasteur, 2010

Protein Folding Symposium, Notre Dame, 2010

GPU Workshop, Lawrence Berkeley National Laboratory, 2010

Biomedical Computation at Stanford (BCATS), Stanford University, 2010

Stanford High Performance Computing Conference, Stanford University, 2010

Teaching

Taught “Constructing an Alternate Universe: Computer Simulations of Protein Folding”, 2008-2010

Ran workshops on MSMBuilder software, 2009-2011

Teaching Assistant for Biophys 242 Methods in Molecular Biophysics, Stanford University, 2009

Mentored rotation students, 2009-2011

California Mentoring Initiative for Youth with Disabilities, 2007-2008

Books

  1. Bowman GR. “An overview and practical guide to building Markov state models” in An introduction to Markov state models and their application to long-timescale molecular simulation. Edited by Bowman GR, Pande VS, and Noe F. Springer Press, in preparation.
  2. Bowman GR. “Tutorial on building Markov state models with MSMBuilder and coarse-graining them with BACE” in Protein dynamics. Edited by Livesay DR. Humana Press, 2013.

Publications (*Corresponding author)

An up-to-date list of publications is always available at my Google scholar page.

  1. Bowman GR*, Meng L, Huang X. Quantitative comparison of alternative methods for coarse-graining biological networks. J Chem Phys 2013, in press.
  2. Yao Y, Cui RZ, Bowman GR, Silva DA, Sun J, Huang X. Hierarchical Nystrom methods for constructing Markov state models for conformational dynamics. J Chem Phys 2013;138:174106.
  3. Bowman GR*, Geissler PL. Extensive structural heterogeneity within protein cores. In preparation.
  4. Kohlhoff KJ, Shukla D, Lawrenz M, Bowman GR, Konerding DE, Altman RB, Pande VS. A new platform for science: Cloud-based millisecond molecular dynamics reveals alternative GPCR deactivation pathways. In preparation.
  5. Qiao Q, Bowman GR, Huang X. Dynamics of an intrinsically disordered protein reveal metastable conformations that potentially seed aggregation. In preparation.
  6. Bowman GR*, Geissler PL. Equilibrium fluctuations of a single folded protein reveal a multitude of potential cryptic allosteric sites. Proc Natl Acad Sci U S A 2012;29:11681-11686.
  7. Bowman, GR*. Improved coarse-graining of Markov state models via explicit consideration of statistical uncertainty. J Chem Phys 2012;137;134111.
  8. Levin AM, Bates DL, Ring AM, Krieg C, Lin JT, Su L, Moraga I, Raeber ME, Bowman GR, Novick P, Pande VS, Fathman CG, Boyman O, Garcia KC. Exploiting a natural conformational switch to engineer an interleukin-2 ‘superkine’. Nature 2012;484:529-533.
  9. Ring AM, Lin J, Feng D, Mitra S, Rickert M, Bowman GR, Pande VS, Li P, Moraga I, Spolski R, Özkan E, Leonard WJ, Garcia KC. Mechanistic and structural insight into the functional dichotomy between IL-2 and IL-15. Nature Immunology 2012;13:1187-1195.
  10. Cui RZ, Silva DA, Song J, Bowman GR, Zhuang W, Huang X. Bridging the gap between optical spectroscopic experiments and computer simulations for fast protein folding dynamics. Curr Phys Chem 2012;2:45-58.
  11. Voelz VA, Jager M, Yao S, Chen Y, Zhu L, Waldauer SA, Bowman GR, Friedrichs M, Bakajin O, Lapidus LJ, Weiss S, Pande VS. Slow unfolded-state structuring in ACBP folding revealed by theory and experiment. J Am Chem Soc 2012;134:12565-12577.
  12. Bowman GR, Voelz VA, Pande VS. Atomistic folding simulations of the five-helix bundle protein λ6-85. J Am Chem Soc 2011;133:664-667.
  13. Bowman GR, Voelz VA, Pande VS. Taming the complexity of protein folding. Curr Opin Struct Biol 2011;21:4-11.
  14. Silva D, Bowman GR, Sosa-Peinado A, Huang X. A role for both conformational selection and induced fit in ligand binding by the LAO protein. PLoS Comput Biol 2011;7:e1002054.
  15. Beauchamp KA, Bowman GR, Lane TJ, Maibaum L, Haque IS, Pande VS. MSMBuilder2: Modeling conformational dynamics at the picosecond to millisecond scale. J Chem Theory Comput 2011;7:3412-3419.
  16. Lane TJ, Bowman GR, Beauchamp KA, Voelz VA, Pande VS. Markov state model reveals folding and functional dynamics in ultra-long MD trajectories. J Am Chem Soc 2011;113:18413-18419.
  17. Lin Y, Bowman GR, Beauchamp KA, Pande VS. Investigating how peptide length and a pathogenic mutation modify the structural ensemble of amyloid beta monomer. Biophys J 2011;102:315-324.
  18. Pronk S, Larsson P, Pouya I, Bowman GR, Haque IS, Beauchamp KA, Hess B, Pande VS, Kasson PM, Lindahl E. Copernicus: A new paradigm for parallel adaptive molecular dynamics. In SC ’11: Proc Conf High Perf Computing, Networking, Storage and Analysis, New York, NY, USA, 2011. ACM.
  19. Bowman GR, Pande VS. Protein folded states are kinetic hubs. Proc Natl Acad Sci U S A 2010;107:10890-10895.
  20. Bowman GR, Huang X, Pande VS. Network models for molecular kinetics and their initial applications to human health. Cell Research 2010;20:622–630.
  21. Bowman GR, Ensign DL, Pande VS. Enhanced modeling via network theory: adaptive sampling of Markov state models. J Chem Theory Comput 2010;6:787-794.
  22. Voelz VA, Bowman GR, Beauchamp KA, Pande VS. Molecular simulation of ab initio protein folding for a millisecond folder NTL9(1-39). J Am Chem Soc 2010;132:1526-1528.
  23. Pande VS, Beauchamp KA, Bowman GR. Everything you wanted to know about Markov state models but were afraid to ask. Methods 2010;52:99-105.
  24. Huang X, Yao Y, Sun J, Bowman GR, Guibas L, Carlsson G, Pande VS. Constructing multi-resolution Markov state models (MSMs) to elucidate RNA hairpin folding mechanisms. Pac Symp Biocomput 2010;15:228-239.
  25. Bowman GR, Beauchamp KA, Boxer G, Pande VS. Progress and challenges in the automated construction of Markov state models for full protein systems. J Chem Phys 2009;131:124101.
  26. Bowman GR, Huang X, Pande VS. Using generalized ensemble simulations and Markov state models to identify conformational states. Methods 2009;49:197-201.
  27. Bowman GR, Pande VS. Simulated tempering yields insight into the low-resolution Rosetta scoring functions. Proteins 2009;74:777-788.
  28. Bowman GR, Pande VS. The roles of entropy and kinetics in structure prediction. PLoS One 2009;4:e5840.
  29. Huang X, Bowman GR, Bacallado S, Pande VS. Rapid equilibrium sampling initiated from nonequilibrium data. Proc Natl Acad Sci U S A 2009; 106:19765-19769.
  30. Voelz VA, Luttmann E, Bowman GR, Pande VS. Probing the nanosecond dynamics of a designed three-stranded beta-sheet with a massively parallel molecular dynamics simulation. Int J Mol Sci 2009;10:1013-1030.
  31. Yao Y, Sun J, Huang X, Bowman GR, Singh G, Lesnick M, Guibas LJ, Pande VS, Carlsson G. Topological methods for exploring low-density states in biomolecular folding pathways. J Chem Phys 2009;130:144115.
  32. Bowman GR, Huang X, Yao Y, Sun J, Carlsson G, Guibas LJ, Pande VS. Structural insight into RNA hairpin folding intermediates. J Am Chem Soc 2008;130:9676-9678.
  33. Huang X, Bowman GR, Pande VS. Convergence of folding free energy landscapes via application of enhanced sampling methods in a distributed computing environment. J Chem Phys 2008;128:205106.
  34. Zwick ME, Mcafee F, Cutler DJ, Read TD, Ravel J, Bowman GR, Galloway DR, Mateczun A. Microarray-based resequencing of multiple Bacillus anthracis isolates. Genome biology 2005;6:R10.