B. Munsky

发表

The finite state projection algorithm for the solution of the chemical master equation.

M. Khammash, B. Munsky, 2006, The Journal of chemical physics.

Using Gene Expression Noise to Understand Gene Regulation

A. van Oudenaarden, B. Munsky, G. Neuert, 2012, Science.

The simplicity of completion time distributions for common complex biochemical processes

I. Nemenman, B. Munsky, G. Bel, 2009, Physical biology.

Transcription Factors Modulate c-Fos Transcriptional Bursts

Brian Munsky, Christophe Zimmer, Xavier Darzacq, 2014, Cell reports.

Stochasticity or Noise in Biochemical Reactions

B. Munsky, Z. Fox, 2017, 1708.09264.

Ribozyme-based insulator parts buffer synthetic circuits from genetic context

Christopher A. Voigt, C. Voigt, B. Munsky, 2012, Nature Biotechnology.

Chapter 11 : Modeling Cellular Variability ∗

B. Munsky, 2011 .

Identification from stochastic cell-to-cell variation: a genetic switch case study.

M. Khammash, B. Munsky, Mustafa Khammash, 2010, IET systems biology.

Transient analysis of stochastic switches and trajectories with applications to gene regulatory networks.

M. Khammash, B. Munsky, 2008, IET systems biology.

Quantifying the dynamics of IRES and cap translation with single-molecule resolution in live cells

Luis U. Aguilera, B. Munsky, T. Morisaki, 2020, Nature Structural & Molecular Biology.

Systematic Identification of Signal-Activated Stochastic Gene Regulation

M. Khammash, A. van Oudenaarden, B. Munsky, 2013, Science.

Induced-shear piezoelectric actuators for rotor blade trailing edge flaps

Edward C. Smith, Brian Munsky, Louis Centolanza, 2002 .

Distribution shapes govern the discovery of predictive models for gene regulation

Brian Munsky, Douglas P. Shepherd, Gregor Neuert, 2017, Proceedings of the National Academy of Sciences.

STOCHASTIC MODELING OF THE PAP PILI EPIGENETIC SWITCH

M. Khammash, B. Munsky, Aaron D Hernday, 2005 .

Analysis of Noise Induced Stochastic Fluctuations in Gene Regulatory Networks

M. Khammash, B. Munsky, 2007 .

A Multiple TimeStep Finite State Projection Algorithm for the Solution to the Chemical Master Equation

Brian Munsky, Mustafa Khammash, M. Khammash, 2006 .

Diverse Cell Stimulation Kinetics Identify Predictive Signal Transduction Models

B. Munsky, G. Neuert, Z. Fox, 2020, bioRxiv.

Diverse Cell Stimulation Kinetics Identify Predictive Signal Transduction Models

B. Munsky, G. Neuert, Z. Fox, 2020, iScience.

Live-cell imaging reveals the spatiotemporal organization of endogenous RNA polymerase II phosphorylation at a single gene

B. Munsky, H. Kimura, T. Morisaki, 2020, Nature Communications.

Integrating single-molecule experiments and discrete stochastic models to understand heterogeneous gene transcription dynamics.

Brian Munsky, Gregor Neuert, B. Munsky, 2015, Methods.

Quantifying the spatiotemporal dynamics of IRES versus Cap translation with single-molecule resolution in living cells

Luis U. Aguilera, B. Munsky, T. Morisaki, 2020, bioRxiv.

Probabilistic Ranking Of Microbiomes Plus Taxa Selection to discover and validate microbiome function models for multiple litter decomposition studies

Marie E. Kroeger, B. Munsky, N. Lubbers, 2020, bioRxiv.

Visualization and modeling of inhibition of IL-1β and TNF-α mRNA transcription at the single-cell level

Huy D. Vo, B. Munsky, H. Vo, 2020, Scientific Reports.

Listeningtothenoise:randomfluctuationsrevealgene network parameters

M. Khammash, B. Munsky, Brooke Trinh, 2009 .

Biochemical noise enables a single optogenetic input to control identical cells to track asymmetric and asynchronous reference signals

B. Munsky, M. May, 2022, bioRxiv.

The finite state projection approach to analyze dynamics of heterogeneous populations

B. Munsky, Rob Johnson, 2017, Physical biology.

Using noise to control heterogeneity of isogenic populations in homogenous environments

B. Munsky, M. Soltani, N. Gritti, 2015, Physical biology.

Optogenetic Maxwell Demon to Exploit Intrinsic Noise and Control Cell Differentiation Despite Time Delays and Extrinsic Variability

B. Munsky, M. May, 2022, bioRxiv.

Guidelines for the Identiﬁcation of a Stochastic Model for the Genetic Toggle Switch

M. Khammash, B. Munsky, 2010 .

From analog to digital models of gene regulation

B. Munsky, G. Neuert, 2015, Physical biology.

Listening to the noise: random fluctuations reveal gene network parameters

Brian Munsky, Mustafa Khammash, Brooke Trinh, 2009, Molecular systems biology.

Specificity and completion time distributions of biochemical processes.

Brian Munsky, Ilya Nemenman, Golan Bel, 2009, The Journal of chemical physics.

Soil Bacterial and Fungal Richness Forecast Patterns of Early Pine Litter Decomposition

Michaeline B. N. Albright, Marie E. Kroeger, B. Munsky, 2020, Frontiers in Microbiology.

Microbial community composition controls carbon flux across litter types in early phase of litter decomposition

Michaeline B. N. Albright, Marie E. Kroeger, B. Munsky, 2021, Environmental microbiology.

Predicting single-cell transcription dynamics even when the central limit theorem fails

Brian Munsky, Douglas P. Shepherd, Gregor Neuert, 2017 .

Non-equilibrium structural dynamics of supercoiled DNA plasmids exhibits asymmetrical relaxation

B. Munsky, D. Levens, C. Benham, 2022, Nucleic acids research.

Using mechanistic models and machine learning to design single-color multiplexed Nascent Chain Tracking experiments

Luis U. Aguilera, B. Munsky, T. Morisaki, 2023, bioRxiv.

Counting small RNA in pathogenic bacteria.

Brian Munsky, Elizabeth Hong-Geller, James H Werner, 2013, Analytical chemistry.

Adaptive coarse-graining for transient and quasi-equilibrium analyses of stochastic gene regulation

Brian Munsky, James R. Faeder, José Juan Tapia, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

Optimal Design of Single-Cell Experiments within Temporally Fluctuating Environments

Brian Munsky, Gregor Neuert, Zachary R Fox, 2019, bioRxiv.

Systems biology and control — A tutorial

Domitilla Del Vecchio, Pablo A. Iglesias, Eduardo D. Sontag, 2007, 2007 46th IEEE Conference on Decision and Control.

Using noise transmission properties to identify stochastic gene regulatory networks

Brian Munsky, Mustafa Khammash, M. Khammash, 2008, 2008 47th IEEE Conference on Decision and Control.

Live-Cell Single RNA Imaging Reveals Bursts of Translational Frameshifting.

Brian Munsky, Luis U. Aguilera, Luis U Aguilera, 2019, Molecular cell.

Building predictive signaling models by perturbing yeast cells with time-varying stimulations resulting in distinct signaling responses

B. Munsky, G. Neuert, Z. Fox, 2021, STAR protocols.

Identification of gene regulation models from single-cell data

William Raymond, Brian Munsky, Lisa Weber, 2017, bioRxiv.

Using Flow Cytometry and Multistage Machine Learning to Discover Label-Free Signatures of Algal Lipid Accumulation

Brian Munsky, Babetta L. Marrone, Mohammad Tanhaemami, 2018, bioRxiv.

Differences in substrate use linked to divergent carbon flow during litter decomposition.

Michaeline B. N. Albright, Marie E. Kroeger, B. Munsky, 2020, FEMS microbiology ecology.

Machine learning to predict microbial community functions: An analysis of dissolved organic carbon from litter decomposition

Brian Munsky, Jaron Thompson, Renee Johansen, 2019, bioRxiv.

Modeling and analysis of a bacterial stochastic switch

M. Khammash, B. Munsky, M. Khammash, 2006, 2006 14th Mediterranean Conference on Control and Automation.

Quantifying the dynamics of IRES and cap translation with single-molecule resolution in live cells

Luis U. Aguilera, B. Munsky, T. Morisaki, 2020, Nature Structural & Molecular Biology.

Reduction and solution of the chemical master equation using time scale separation and finite state projection.

Brian Munsky, Mustafa Khammash, Slaven Peles, 2006, The Journal of chemical physics.

Microbial Communities Influence Soil Dissolved Organic Carbon Concentration by Altering Metabolite Composition

Michaeline B. N. Albright, B. Munsky, V. Bailey, 2022, Frontiers in Microbiology.

Analysis and design of single-cell experiments to harvest fluctuation information while rejecting measurement noise

Huy D. Vo, Luis U. Aguilera, B. Munsky, 2021, bioRxiv.

Exploiting noise, non-linearity, and feedback for differential control of multiple synthetic cells with a single optogenetic input

B. Munsky, M. May, 2021, bioRxiv.

Bayesian estimation for stochastic gene expression using multifidelity models

Brian Munsky, Huy D. Vo, Zachary Fox, 2018, bioRxiv.

Bayesian Estimation for Stochastic Gene Expression Using Multifidelity Models.

Brian Munsky, Huy D. Vo, Zachary Fox, 2019, The journal of physical chemistry. B.

The finite state projection based Fisher information matrix approach to estimate information and optimize single-cell experiments

Brian Munsky, Zachary Fox, B. Munsky, 2018, bioRxiv.

The Fifth Annual q-bio Conference on Cellular Information Processing

Brian Munsky, Ilya Nemenman, Tomasz Lipniacki, 2012 .

Adsorption-Coupled Diffusion of Gold Nanoclusters within a Large-Pore Protein Crystal Scaffold.

C. Snow, B. Munsky, C. Ackerson, 2017, The journal of physical chemistry. B.

Computational design and interpretation of single-RNA translation experiments

William Raymond, Brian Munsky, Luis U. Aguilera, 2019, bioRxiv.

Live-cell single RNA imaging reveals bursts of translational frameshifting

Brian Munsky, Luis U. Aguilera, Tatsuya Morisaki, 2018, bioRxiv.

A Parallel Implementation of the Finite State Projection Algorithm for the Solution of the Chemical Master Equation

Brian Munsky, Huy D. Vo, Huy Vo, 2020, bioRxiv.

BAYESIAN INFERENCE OF STOCHASTIC REACTION NETWORKS USING MULTIFIDELITY SEQUENTIAL TEMPERED MARKOV CHAIN MONTE CARLO.

Brian Munsky, Thomas A. Catanach, Huy D. Vo, 2020, International journal for uncertainty quantification.

A multiple time interval finite state projection algorithm for the solution to the chemical master equation

Brian Munsky, Mustafa Khammash, M. Khammash, 2007, J. Comput. Phys..

Systematic Identification of Signal-Activated Stochastic Gene Regulation

M. Khammash, A. van Oudenaarden, B. Munsky, 2013, Science.

Finite state projection based bounds to compare chemical master equation models using single-cell data.

Brian Munsky, Gregor Neuert, Zachary Fox, 2016, The Journal of chemical physics.

The Finite State Projection Approach for the Analysis of Stochastic Noise in Gene Networks

Brian Munsky, Mustafa Khammash, M. Khammash, 2008, IEEE Transactions on Automatic Control.

The Finite State Projection approach for the solution of the master equation and its applications to stochastic gene regulatory networks

Brian E. Munsky, B. Munsky, 2008 .

Using mechanistic models and machine learning to design single-color multiplexed nascent chain tracking experiments

Luis U. Aguilera, B. Munsky, T. Morisaki, 2023, Frontiers in Cell and Developmental Biology.

The finite state projection based Fisher information matrix approach to estimate information and optimize single-cell experiments

B. Munsky, Z. Fox, 2018, bioRxiv.

Stochastic analysis of gene regulatory networks using finite state projections and singular perturbation

M. Khammash, B. Munsky, S. Peles, 2007, 2007 American Control Conference.

A reduced model solution for the chemical master equation arising in stochastic analyses of biological networks

M. Khammash, B. Munsky, M. Khammash, 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

Stochastic Gene Expression: Modeling, Analysis, and Identification *

M. Khammash, B. Munsky, 2022 .

Ten simple rules for managing laboratory information

D. Densmore, B. Munsky, N. Hillson, 2023, PLoS Comput. Biol..

Quantitative Biology: Theory, Computational Methods, and Models

Terrence J. Sejnowski, Alan S. Perelson, Marco S. Nobile, 2018 .

Perspective on the q-bio Summer School and Conference: 2007–2014 and beyond

William S. Hlavacek, Brian Munsky, Orna Resnekov, 2014, Quantitative Biology.

Designing single-cell experiments to harvest fluctuation information while rejecting measurement noise

Huy D. Vo, B. Munsky, 2022 .

Designing single-cell experiments to harvest fluctuation noise while rejecting measurement noise

Huy D. Vo, B. Munsky, 2021 .