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Petr Sulc

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Center for Biological Physics
Assistant Professor
Faculty, TEMPE Campus, Mailcode 7301
Biodesign Center for Biocomputing, Security and Society
Faculty Member
Faculty, TEMPE Campus, Mailcode 7301
School of Molecular Sciences
Assistant Professor
Faculty, TEMPE Campus, Mailcode 7301
Biodesign Center for Molecular Design & Biomimetics
Assistant Professor
Faculty, TEMPE Campus, Mailcode 7301
Biography: 

Petr Šulc’s research focuses on application of computational modeling and statistical physics approaches to complex systems. In particular, his group uses computational models to study problems in biology, and bio-inspired nanotechnology systems. He is mainly interested in nucleic acids modeling (DNA and RNA) using coarse-grained models, which allow for simulations of longer time-scales and larger systems than if fully-atomistic representation is used. Such an approach is allows for efficient studies of nanotechnology system, as well as biologically relevant interactions between nucleic acids.

His research group is furthermore interested in applying computer simulations and statistical physics analysis to study properties of RNA molecules in vivo, in relation to RNAs expressed in tumor cells and viral genomes. The research is done in active collaboration with experimental groups.

He is an assistant professor at ASU. Prior to ASU, he was a fellow in physics and biology with The Rockefeller University (2014-2017) and served as a graduate research assistant with the Center for Nonlinear Studies at the Los Alamos National Laboratory, New Mexico (2009-2010). His prior research also involved mathematical modeling and optimization of smart-grid systems.

Education: 
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Research Interests: 

Petr Sulc's research focuses on application of computational modeling  / statistical physics approaches to complex systems. In particular, his group uses computational models to study problems in biology, and bio-inspired nanotechnology systems. He is mainly interested in nucleic acids modeling (DNA and RNA) using coarse-grained models, which allow for simulations of longer time-scales and larger systems than if fully-atomistic representation is used. Such an approach is allows for efficient studies of nanotechnology system, as well as biologically relevant interactions between nucleic acids.

His research group is furthermore interested in applying computer simulations and statistical physics analysis to study properties of RNA molecules in vivo, in relation to RNAs expressed in tumor cells and viral genomes.  The research is done in active collaboration with experimental groups.

His prior research also involved mathematical modeling and optimization of smart-grid systems.

Publications: 
  1. Nanobase.org: a repository for DNA and RNA nanostructures.  Nucleic Acids Research (2022).  E. Poppleton, A. Mallya, S. Dey, J. Joseph, P. Šulc.
  2. Unified Nanotechnology Format: One Way to Store Them All.  Molecules (2021).  D. Kuťák, E. Poppleton, H. Miao, P. Šulc, I. Barišić.
  3. Kinetics of RNA and RNA:DNA Hybrid Strand Displacement.  ACS Synth. Biol. (2021).  H. Liu, F. Hong, F. Smith, J. Goertz, T. Ouldridge, M.M. Stevens, H. Yan, P. Šulc.
  4. A Self-Regulating DNA Rotaxane Linear Actuator Driven by Chemical Energy.  J. Am. Chem. Soc. (2021).  Z. Yu, M. Centola, J. Valero, M. Matthies, P. Šulc, M. Famulok.
  5. OxDNA.org: a public webserver for coarse-grained simulations of DNA and RNA nanostructures.   Nucleic Acids Research (2021).  E. Poppleton, R. Romero, A. Mallya, L. Rovigatti, P. Šulc.
  6. A Primer on the oxDNA Model of DNA: When to Use it, How to Simulate it and How to Interpret the Results.  Frontiers in Molecular Biosciences (2021).  A. Sengar, T.E. Ouldridge, O. Henrich, L. Rovigatti, P. Šulc.
  7. The Heterogeneous Landscape and Early Evolution of Pathogen-Associated CpG Dinucleotides in SARS-CoV-2.  Cell Reports Physical Science (2021).  A. Di Gioacchino, P. Šulc, A.V. Komarova, B.D. Greenbaum, R. Monasson, S. Cocco.
  8. Coarse-grained nucleic acid–protein model for hybrid nanotechnology.  Soft Matter (2021).  J. Procyk, E. Poppleton, P. Šulc.
  9. DNA Nanodevices as Mechanical Probes of Protein Structure and Function.  Applied Sciences (2021).  N. Stephanopoulos, P. Šulc.  
  10. Meta-DNA Structures.  Nature Chemistry (2020).  G. Yao, F. Zhang, F. Wang, T. Peng, H. Liu, E. Poppleton, P. Šulc, S. Jiang, L. Liu, C. Gong, X. Jing, X. Liu, L. Wang, Y. Liu, C. Fan, H. Yan.
  11. The Multiscale Future of RNA Modeling.  Biophysical Journal (2020).  P. Šulc.  
  12. Design, optimization and analysis of large DNA and RNA nanostructures through interactive visualization, editing and molecular simulation.  Nucleic Acids Research (2020).  E. Poppleton, J. Bohlin, M. Matthies, S. Sharma, F. Zhang, P. Sulc.
  13. Designing Patchy Interactions to Self-Assemble Arbitrary Structures.  Physical Review Letters (2020).  F. Romano, J. Russo, L. Kroc, P. Sulc.
  14. Triangulated Wireframe Structures Assembled Using Single-Stranded DNA Tiles.  ACS Nano (2019).  M. Matthies, N.P. Agarwal, E. Poppleton, F.M. Joshi,  P. Sulc, T.L. Schmidt.
  15. An emergent understanding of strand displacement in RNA biology.  Journal of Structural Biology (2019).  F. Hong, P. Sulc.
  16. Triangulated Wireframe Structures Assembled Using Single-Stranded DNA Tiles.  ACS Nano (2019).  M. Matthies, N.P. Agarwal, E. Poppleton, F.M. Joshi, P. Sulc, T.L. Schmidt.
  17. Introduction to Molecular Simulation.  Quantitative Biology (2018), a book chapter.  P. Šulc, J. Doye, A. Louis
  18. Layered-crossover tiles with precisely tunable angles for 2D and 3D DNA crystal engineering.  Journal of the American Chemical Society (2018).  F. Hong, S. Jiang, X. Lan, R.P. Narayanan, P. Šulc, F. Zhang, Y. Liu, H. Yan.
  19. Rapid Photoactuation of a DNA nanostructure using an internal photocaged trigger stand.  Angewandte Chemie (2018).  M. Liu, S. Jiang, O. Loza, N.E. Fahmi, P. Šulc, N. Stephanopoulos.
  20. Layered-Crossover Tiles with Precisely Tunable Angles for 2D and 3D DNA Crystal Engineering.  Journal of American Chemical Society (2018) F. Hong, S. Jiang, X. Lan, R.P. Narayanan, P. Sulc, F. Zhang, Y. Liu, H. Yan.
  21. Self-assembling DNA nanotube to connect molecular landmark.  Nature nanotechnology (2017).  A. M. Mohammed, P. Šulc, J. Zenk, R. Schulman.
  22. Coarse-grained modelling of supercoiled RNA.  J. Chem. Phys., 143 243122 (2015) preprint:  arXiv:1506.02539.  C. Matek, P. Šulc, F. Randisi, J.P.K. Doye, A. A. Louis.
  23. Introducing Improved Structural Properties and Salt Dependence into a Coarse-Grained Model of DNA.  J. Chem. Phys., 142, 234901 (2015) (article featured on the journal cover) , preprint:  arXiv:1504.00821.  B. E. K. Snodin, F. Randisi, M. Mosayebi, P. Šulc, J. S. Schreck, F. Romano, T. E. Ouldridge, R. Tsukanov, E. Nir, A. A. Louis, J. P. K. Doye.
  24. Modeling toehold-mediated RNA strand displacement.  Biophys. J. 108, iss. 5, 1238-1247 (2015) (article featured on the front cover), preprint:  arXiv:1411.3239.  P. Šulc, T. E. Ouldridge, F. Romano, J. P. K. Doye, A. A. Louis.
  25. DNA hairpins primarily promote duplex melting rather than inhibiting hybridization.  Nucleic Acids Res. (2015) preprint:  arXiv: 1408.4401.  J. S. Schreck, T. E. Ouldridge, F. Romano, P. Šulc, L. Shaw, A. A. Louis, J. P. K. Doye.
  26. A nucleotide-leve coarse-grained model of RNA.  J. Chem. Phys. 140, 235102 (2014) (article featured on the front cover), preprint: arXiv:1403.4180.  P. Šulc, F. Romano, T. E. Ouldridge, J. P. K. Doye, A. A. Louis.
  27. A comparison between parallelization approaches in molecular dynamics simulations on GPUs.  J. Comp. Chem 36 (2015), (article featured on the front cover) preprint: arXiv:1401.4350.  L. Rovigatti, P. Šulc, István Z. Reguly, F. Romano.
  28. Optimal Distributed Control of Reactive Power via the Alternating Directon Method of Multipliers.  IEEE Transactions on Energy Conversion 29 (2014), preprint: arXiv:1310.5748.  P. Šulc, S. Backhaus, M. Chertkov.
  29. Coarse-graining DNA for simulations of DNA nanotechnology.  Phys. Chem. Chem. Phys. (2013), preprint:  arXiv:1308.3843.  J.P.K. Doye, T. E. Ouldridge, A. A. Louis, F. Romano, P. Šulc, C. Matek, B.E.K. Snodin, L. Rovigatti, J. S. Schreck, R.M. Harrison, W.P.J. Smith.
  30. On the biophysics and kinetics of toehold-mediated DNA strand displacement.  Nucleic Acids Res. (2013) 
    N. Srinivas, T.E. Ouldridge, P. Šulc, J.M. Schaeffer, B. Yurke, A.A. Louis, J.P.K. Doye, E. Winfree.
  31. DNA hybridization kinetics:  zippering, internal displacement and sequence dependence.  Nucleic Acids Res. (2013), preprint: arXiv: 1303.3370.  T.E. Ouldridge, P. Šulc, F. Romano, J.P.K. Doye, A.A. Louis.
  32. Simulating a burnt-bridges DNA motor with a coarse-grained DNA model.  Natural Computing (2014), preprint: arXiv: 1212.4536.  P. Šulc, T.E. Ouldridge, F. Romano, J.P.K. Doye, A.A. Louis. 
  33. Sequence-dependent thermodynamics of a course-grained DNA model.  J. Chem. Phys. (2012), (article featured on the front cover) preprint: arXiv: 1207.3391.  P. Šulc, F. Romano, T.E. Ouldridge, L. Rovigatti, J.P.K. Doye, A.A. Louis.
  34. Non-Gaussianity in single-particle tracking:  Use of kurtosis to learn the characteristics of a cage-type potential.  
    Phys. Rev. E (2012), preprint: arXiv: 1102.2290.  P. Lushnikov, P. Šulc, K. Turitsyn.
  35. Options for Control of Reactive Power by Distributed Photovoltaic Generators.  Proceedings of the IEEE (2011), preprint: arXiv: 1008.0878.  K. Turitsyn, P. Šulc, S. Backhaus, M. Chertkov.
  36. Local Control of Reactive Power by Distributed Photovoltaic Generators.  IEEE SmartGridComm 2010, preprint: arXiv: 1006.0160.  K. Turitsyn, P. Šulc, S. Backhaus, M. Chertkov.
  37. Belief propagation for graph partitioning.  Journal of Physics A: Math. & Theor. (2010), preprint: arXiv: 0912.3563.  P. Šulc, L. Zdeborová.
  38. Distributed control of reactive power flow in a radial distribution circuit with high photovoltaic penetration.  IEEE Power and Energy Society General Meeting 2010, preprint: arXiv: 0912.3281.  K. Turitsyn, P. Šulc, S. Backhaus, M. Chertkov.
  39. Quantifying Slow Evolutionary Dynamics in RNA Fitness Landscapes.  Journal of Bioinformatics and Computational Biology, (2010), preprint: arXiv: 0911.5366.  P. Šulc, O. C. Martin, A. Wagner.
  40. Random walk return probabilities and hitting times on sparse Erdos-Renyi graphs.  Phys. Rev. E 81, (2010), preprint: arXiv: 0902.2173.  O. C. Martin, P. Šulc.
  41. Group theoretical construction of mutually unbiased bases in Hilbert spaces of prime dimensions.  Journal of Physics A: Math. & Theor. (2007), preprint: arXiv: 0708.4114.  P. Šulc, J. Tolar.
Summer 2022
Course NumberCourse Title
BDE 792Research
BDE 795Continuing Registration
Spring 2022
Course NumberCourse Title
CHM 341Elementary Physical Chemistry
BDE 792Research
BDE 795Continuing Registration
BDE 799Dissertation
Fall 2021
Course NumberCourse Title
CHM 494Special Topics
CHM 598Special Topics
BDE 792Research
BDE 799Dissertation
Summer 2021
Course NumberCourse Title
BDE 792Research
Spring 2021
Course NumberCourse Title
CHM 341Elementary Physical Chemistry
BDE 792Research
BDE 799Dissertation
Fall 2020
Course NumberCourse Title
CHM 341Elementary Physical Chemistry
Summer 2020
Course NumberCourse Title
BDE 792Research
Spring 2020
Course NumberCourse Title
CHM 240Math Methods in Chemistry
BDE 792Research
BDE 799Dissertation
Fall 2019
Course NumberCourse Title
CHM 501Current Topics in Chemistry
CHM 598Special Topics
Spring 2019
Course NumberCourse Title
CHM 240Math Methods in Chemistry
BDE 792Research
BDE 799Dissertation
Spring 2018
Course NumberCourse Title
CHM 240Math Methods in Chemistry
Expertise Areas: 
Chemistry
Computational Biology
Computational Modeling
Molecular Biophysics
Physics