(+) Selected Publications
  • HD Vo, LS Forero-Quintero, LU Aguilera, B Munsky, "Analysis and design of single-cell experiments to harvest fluctuation information while rejecting measurement noise," Frontiers in Cell and Developmental Biology, 11, 1133994, 2023, https://doi.org/10.3389/fcell.2023.1133994
  • L. Forero, W. Raymond, T. Handa, M. Saxton, T. Morisaki, H. Kimura, E. Bertrand, B. Munsky*T. Stasevich*, "Live-cell imaging reveals the spatiotemporal organization of endogenous RNA polymerase II phosphorylation at a single gene", Nature Communications, https://doi.org/10.1101/2020.04.03.024414
  • A L Koch, L Aguilera, T Morisaki, B E Munsky*, T J Stasevich*, "Quantifying the spatiotemporal dynamics of IRES versus Cap translation with single-molecule resolution in living cells,"
  • K.R. Lyon Jr., L.U. Aguilera, T. Morisaki, B. Munsky*, T.J. Stasevich*, Live-cell single RNA imaging reveals bursts of translational frameshifting, Molecular Cell, 178:2, 2019, https://doi.org/10.1016/j.molcel.2019.05.002
  • L. Aguilera, W. Raymond, Z. R. Fox, M. P. May, E. Djokic, T. Morisaki, T. J. Stasevich, B. Munsky, Computational design and interpretation of live-cell, single-RNA translation experiments, PLoS Computational Biology, 15:10, e1007425, 2019, https://doi.org/10.1371/journal.pcbi.1007425
  • J. Thompson, R. Johansen, J. Dunbar, B. Munsky, Machine learning to predict microbial community functions: An analysis of dissolved organic carbon from litter decomposition, PLoS One, 14:7, e0215502, 2019, https://doi.org/10.1371/journal.pone.0215502
  • Z. Fox, B. Munsky, The finite state projection based Fisher information matrix approach to estimate and maximize the information in single-cell experiments, PLoS Computational Biology15:1, e1006365, 2019, online here
  • G Neuert, B Munsky, R-Z Tan, L Teytelman, M Khammash, A van Oudenaarden, Systematic Identification of Signal-Activated Stochastic Gene Regulation, Science339:6119, 584-587 (2013). reprint (.pdf)
  • Munsky, B., Khammash, M., The Finite State Projection Algorithm for the Solution of the Chemical Master Equation, Journal of Chemical Physics124 :044104 (2006). reprint (.pdf)
(+) 2021
  • D Kalb+, H D. Vo+ , S Adikari3, E Hong-Geller3, B Munsky*, J  Werner*, "Visualization and Modeling of Inhibition of IL-1β and TNFα mRNA Transcription at the Single-Cell Level," bioRxiv, 2020, https://doi.org/10.1101/2020.10.16.342576 (+contributed equally),
  • L. Forero, W. Raymond, T. Handa, M. Saxton, T. Morisaki, H. Kimura, E. Bertrand, B. Munsky*T. Stasevich*, "Live-cell imaging reveals the spatiotemporal organization of endogenous RNA polymerase II phosphorylation at a single gene", Nature Communications, in press, https://doi.org/10.1101/2020.04.03.024414
(+) 2020
(+) 2019
  • L. Aguilera, W. Raymond, Z. R. Fox, M. P. May, E. Djokic, T. Morisaki, T. J. Stasevich, B. Munsky, Computational design and interpretation of live-cell, single-RNA translation experiments, PLoS Computational Biology, 15:10, e1007425, 2019, https://doi.org/10.1371/journal.pcbi.1007425
  • J. Thompson, R. Johansen, J. Dunbar, B. Munsky, Machine learning to predict microbial community functions: An analysis of dissolved organic carbon from litter decomposition, PLoS One, 14:7, e0215502, 2019, online here
  • Z. Fox, B. Munsky, The finite state projection based Fisher information matrix approach to estimate and maximize the information in single-cell experiments, PLoS Computational Biology15:1, e1006365, 2019, online here
  • H.D. Vo, Z.R. Fox, A. Baetica, B. Munsky, Bayesian estimation for stochastic gene expression using multifidelity models, J Physical Chemistry B, 123:10, 2217-2234, 2019, online here
  • M. Tanhaemami, E. Alizadeh, C. Sanders, B. Marrone, B. Munsky, Using Flow Cytometry and Multistage Machine Learning to Discover Label-Free Signatures of Algal Lipid Accumulation, Physical Biology, 16, 055001, 2019, online here
  • K.R. Lyon Jr., L.U. Aguilera, T. Morisaki, B. Munsky, T.J. Stasevich, Live-cell single RNA imaging reveals bursts of translational frameshifting, Molecular Cell, 178:2, 458-472.e19, 2019, online here
(+) 2018
  • B. Munsky, G. Li, Z. Fox, D. P Shepherd, G. Neuert, Distribution shapes govern the discovery of predictive models for gene regulation, Proceedings of the National Academy of Sciences USA, 115:29, 7533-7538 (2018), online here
  • L Weber, W Raymond, B Munsky, Identification of Gene Regulation Models from Single-Cell Data, Physical Biology, 15:5 (2018). online here
  • Z Fox, B Munsky, Stochasticity or Noise in Biochemical Reactions, To appear in Quantitative Biology: Theory, Computational Methods and Examples of Models, edited by B Munsky, L S Tsimring, and W S Hlavacek, MIT Press, ch. 5 (2018). get exam copy or purchase here , get arXiv version
  • L Weber, W Raymond, B Munsky, Tutorial on the Identification of Gene Regulation Models from Single-Cell Data, To appear in Quantitative Biology: Theory, Computational Methods and Examples of Models, edited by B Munsky, L S Tsimring, and W S Hlavacek, MIT Press, ch. 30 (2018). get exam copy or purchase here
  • Quantitative Biology: Theory, Computational Methods and Examples of Models, edited by B Munsky, L S Tsimring, and W S Hlavacek, MIT Press, (2018). get exam copy or purchase here
(+) 2017
  • R. Johnson and B. MunskyThe finite state projection approach to analyze dynamics of heterogeneous populations, Physical Biology, 14:3, 035002 (2017), online here
  • L.F. Hartje, B. Munsky, T.W. Ni, CJ Ackerson, C.D. Snow, Adsorption-Coupled Diffusion of Gold Nanoclusters Within a Large-Pore Protein Crystal Scaffold, J Physical Chemistry B, 121:32, 7652-7659 (2017), PubMed Entry
(+) 2014 - 2016

2016

  • Z. Fox, G. Neuert and B. MunskyFinite state projection based bounds to compare chemical master equation models using single-cell data, Journal of Chemical Physics, 145:7, 074101 (2016), online here

2015

  • P. Szymanska, N. Gritti, J. M. Keegstra, M. Soltani and B. MunskyUsing noise to control heterogeneity of isogenic populations in homogenous environments, Physical Biology, 12:4, 045003 (2015), online here
  • B. Munsky, Z. Fox, G. Neuert, Integrating Single-Molecule Experiments and Discrete Stochastic Models to Understand Heterogeneous Gene Transcription, Methods, 85, 12-21, (2015), online here
  • B. Munsky, G. Neuert, From analog to digital models of gene regulation, Physical Biology, 12:4, 045004, (2015), online here

2014

  • A Senecal, B Munsky, F Proux, N Ly, FE Braye, C Zimmer, F Mueller, X Darzacq, Transcription Factors Modulate c-Fos Transcriptional Bursts, Cell Reports, 8:1, 75-83 (2014), online here
  • O Resnekov, B Munsky, WS Hlavacek, Perspective on the q-bio Summer School and Conference: 2007-2014 and beyond, Quantitative Biology, 2:1, 54-58, online here
(+) 2010 - 2013 (Postdoc) 

2013

  • D Shepherd, N Li, S N Micheva-Viteva, B Munsky, E Hong-Geller, J H Werner, Counting Small RNA in Pathogenic Bacteria, Analytical Chemistry, 85:10, 4938-4943 (2013) (Cover Article), reprint (.pdf)
  • G Neuert, B Munsky, R-Z Tan, L Teytelman, M Khammash, A van Oudenaarden, Systematic Identification of Signal-Activated Stochastic Gene Regulation, Science, 339:6119, 584-587 (2013). reprint (.pdf)
  • Nemenman, I., Gnanakaran, S.,Munsky, B., Wall, M.E., Jiang, Y., Hlavacek, W.S., Faeder. J. The Fifth Annual q-bio Conference on Cellular Information Processing, Physical Biology, 9:050201, 2012. reprint (.pdf)

2012

  • Munsky, B., Neuert, G., van Oudenaarden, A., Using Gene Expression Noise to Understand Gene Regulation, Science, 336:6078, 183-187, (2012). reprint (.pdf)
  • Lou, C., Stanton, B., Chen, Y-C., Munsky, B., Voigt, C. A., Ribozyme-based "insulator parts" buffer synthetic circuits from genetic context, Nature Biotechnology, 30:11, 1137-1142 (2012). reprint (.pdf)
  • Munsky, B.Modeling Cellular Variability, in Quantitative Biology From Molecular to Cellular Systems, pp. 234-266, M. Wall, Ed. (Taylor & Francis Group, New York, 2012). preprint (.pdf)
  • DP Shepherd, N Li, E Hong-Geller, B Munsky, JH Werner, New tools for discovering the role sRNA plays in cellular regulation, Proc. SPIE, 8228:822808, (2012). preprint (.pdf)
  • Tapia, J., Faeder, J., Munsky, B., Adaptive Coarse-Graining for Transient and Quasi-Equilibrium Analyses of Stochastic Gene Regulation, Proc. of the 51st IEEE Conference on Decision and Control, 5361-5366, Maui, HI, Dec. 2012. reprint (.pdf)
  • Nemenman, I., Gnanakaran, S., Hlavacek, W., Jiang, Y., Munsky, B., Wall, M., Faeder. J. The Fifth Annual q-bio Conference on Cellular Information Processing, Physical Biology, 9:050201, 2012. reprint (.pdf)

2010

  • Bel, G., Munsky, B., Nemenman, I., Simplicity of Completion Time Distributions for Common Complex Biochemical Processes, Physical Biology, 7:016003 (2010). reprint (.pdf)
  • Munsky, B., Khammash, M., Identification from stochastic cell-to-cell variation: A genetic switch case study, IET Systems Biology, 4:6, 356-366 (2010). reprint (.pdf)
  • Khammash, M. Munsky, B., Stochastic Gene Expression: Modeling, Analysis, and Identification, in The Control Handbook, B. Levine, Ed. (Taylor & Francis Group, New York, NY, Second Edition, 2010). preprint (.pdf)
 
(+) 2006 - 2009 (Grad School)

2009

  • Munsky, B., Trinh, B., Khammash, M., Listening to the Noise: Random Fluctuations Reveal Gene Network Parameters, Molecular Systems Biology, 5:318 (2009). reprint (.pdf) [Journal Site]
  • Munsky, B., Nemenman, I. Bel, G., Specificity and Completion Time Distributions of Biochemical Processes, Journal of Chemical Physics, 131, No. 235104 (2009). reprint (.pdf)

2008

  • Munsky, B., Khammash, M., The FSP Approach for the Analysis of Stochastic Noise in Gene Networks, IEEE Transactions on Automatic Control, 53, 201-214 (2008). reprint (.pdf)
  • Munsky, B., Khammash, M., Transient Analysis of Stochastic Switches and Trajectories with Applications to Gene Regulatory Networks, IET Systems Biology, 2, No. 2, 323-333 (2008).[.pdf] [IEEE Site]
  • Munsky, B., Khammash, M., Using Noise Transmission Properties to Identify Stochastic Gene Regulatory Networks, Proc. 46th IEEE Conference on Decision and Control, Cancun, Mexico (2008).[.pdf]
  • Munsky, B., Khammash, M., Computation of Switch Time Distributions in Stochastic Gene Regulatory Networks, Proc. 2008 American Control Conference, THB10.2, Seattle, WA.[.pdf]

2007

  • Inglesias, P., Khammash, M., Munsky, B., Sontag, E., Del Vecchio, D., Systems Biology and Control - A Tutorial, Proc. 45th IEEE Conference on Decision and Control, New Orleans, LA (2007).[.pdf]
  • Munsky, B., Khammash, M., A Multiple Time Interval Finite State Projection Algorithm for the Solution to the Chemical Master Equation, Journal of Computational Physics, 226, 818-835 (2007).[.pdf]
  • Munsky, B., Peles, S., Khammash, M., Stochastic analysis of gene regulatory networks using finite state projections and singular perturbation, Proc. 2007 American Control Conference, 1323-1328 (2007). [.pdf]
  • Munsky, B., Khammash, M., Analysis of Noise Induced Stochastic Fluctuations in Gene Regulatory Networks , J. SICE, 5, 405-411 (2007).[.pdf]
  • Peles, S., Munsky, B., Khammash, M., Reduction and Solution of the Chemical Master Equation Using Time Scale Separation and Finite State Projection, Journal of Chemical Physics, 125, 204104 (2007).[.pdf]

2006

  • Munsky, B., Khammash, M., The Finite State Projection Algorithm for the Solution of the Chemical Master Equation, Journal of Chemical Physics, 124 :044104 (2006). reprint (.pdf)
  • Munsky, B., Khammash, M., A Reduced Model Solution for the Chemical Master Equation Arising in Stochastic Analyses of Biological Networks, Proc. 45th IEEE Conference on Decision and Control, San Diego, CA (2006).[.pdf]
  • Munsky, B., Khammash, M., The Finite State Projection Algorithm for the Solution of the Chemical Master Equation, Journal of Chemical Physics, 124 , 044104 (2006).[.pdf]
  • Khammash, M., Munsky, B.Systems Theory Applications in Biology: From Stochastic Chemical Kinetics to Deterministic Model Invalidation, Invited paper-European Control Conference, Kos, Greece (2007).[.pdf]