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John Tyson

Professor, Bilogical Sciences
tyson
5088 Derring Hall (MC 0406)
1405 Perry Street
Blacksburg, VA 24061
  • Lab Phone:: (540) 231-5958
  • Lab 2 Phone: (540) 231-5508

Major Fields of Interest

Systems Biology, Computational Cell Biology, Cell Cycle Regulation, Signal Transduction Network

  • B.S., Chemistry, Wheaton College, 1969
  • Ph.D., Chemical Physics, University of Chicago, 1973
  • Postdoctoral Research Fellow, Max-Planck-Institue for Biophysical Chemistry, Germany, 1973 - 1974
  • Postdoctoral Research, Institute for Biochemistry and Experimental Cancer Research, University of Innsbruck, Austria, 1976 - 1977

Current Research

Cell cycle regulation in budding yeast; estrogen responsiveness in breast cancer cells; innate immune responses; stochastic modeling of protein regulatory networks; cell division control in alpha-proteobacteria

Systems Biology of Cell Cycle Control in Eukaryotes - The cell division cycle (G1->S->G2->M->G1) is not an autonomous oscillator; the transitions between stages are guarded by checkpoints and behave like irreversible bistable switches. We study how such switches emerge from the network and how checkpoint mechanisms use them to maintain genomic integrity.

Functional Motifs in Cellular Regulatory Networks - Complex control networks can be decomposed into simple motifs that carry out specific functions in a cell, such as signal transduction, noise suppression, homeostasis, oscillations, toggle switch, logic gate, cock-and-fire, and adaptation. We use bifurcation theory to analyze these motifs.

The "Standard Component Modeling" Strategy - We assign components according to their time scales into three classes of variables, each described by a different rate law: ODE for protein synthesis/degradation, soft-Heaviside function H(x)=1/(1+exp(-x)) for post-translational modification, and algebraic equation for complex formation. They then serve as “building blocks” for modeling complex protein networks.

Budding Yeast Model - The molecular machinery of eukaryotic cell cycle control is known in greater detail for the budding yeast, Saccharomyces cerevisiae, than for any other organism. This mathematical model helps build confidence in our current understanding while giving direction for future study

Model of the START Transition in the budding yeast - We have updated the 2004 budding yeast model (Mol. Biol. Cell 15:3841) to include a more detailed and accurate descripiton of the START transition. We modeled the regulation of SBF and MBF by Cdk kinases, Bck2, and Whi5, and the effect of phosphorylation of Whi5, Swi4, and Swi6 on the timing of the START transition.

Comprehensive Model of the Budding Yeast Cell Cycle - We modify the regulation of mitotic exit to include the roles of Cdc5 and MEN pathway in triggering Cdc14 release. We integrate both the START and the mitotic exit modules into a full budding yeast model. Our model provides a unified account of the observed phenotypes of 257 mutant strains (98% of the data setused to constrain the model) and new insights into how the cell division cycle is regulated in budding yeast

Generic Cell Cycle Model - This is a mathematical model of the conserved control mechanisms of eukaryotic cells, including budding yeast, fission yeast, Xenopus embyos and mammalian cells.

Automatic Parameter Estimation for the Budding Yeast Model - This is a challenging problem - the control network is complex with 100+ variables and 200+ parameters, and the data available (viabilities of mutants) are qualitative. We devise a strategy combining Latin Hypercube Sampling and Genetic Algorithm. Our approach yields fruitful results.

Stochastic Models of the Budding Yeast Cell Cycle - Moleuclar noises can have a significant effect on the dynamic properties of a regulatory network. We are evaluating approximation methods for the standard Gillespie's algotithm for efficient stochastic simulation, using the budding yeast cell cycle control network as a test case

Estrogen Signaling in Breast Cancer Cells - We present preliminary mathematical models of the basic decision circuits of cell cycle regulation in breast cancer cells. Such models (Tavassoly et al. 2015, Chen et al. 2014, 2013, Parmar et al. 2013, Clarke et al. 2012, Tyson et al. 2011) may aid our understanding of their susceptibility or resistance to endocrine therapy.

T Cell Differentiation - Pathogen-driven differentiation of CD4+ T cells is often heterogeneous in terms of the induced phenotypic diversity. At least four distinct lineages play diverse roles in the immune system. Our model can reproduce known properties of differentiation of CD4+ T cells, such as heterogeneous differentiation of TH1-TH2, TH1-TH17 and iTReg-TH17 under single or mixed types of stimuli.

The Core Model of Caulobacter crescentus Cell Cycle Control is conjectured as a CtrA master-regulator switch that drives the asymmetric cell division. We further investigate the role of dynamical localization of DivL and PleC in the establishment of cellular asymmetry.

Circadian Rhythm Database - We surf around the molecular basis of the circadian rhythm of the fruit fly, and see how the experimental data can be put together as a model, and simulated.

PET - The parameter estimation toolkit pushes the envelope of systems biology software tools by providing cutting edge technology for mathematical simulations and parameter estimation

JigCell - Problem-solving environments can greatly facilitate the development of complex models of biological systems. JigCell is both a platform for experimenting with software solutions that aid computational biologists as well as a practical environment that currently benefits the computational biologist.

Laomettachit, T., Chen, K.C., Baumann, W.T., and Tyson, J.J. (2016). A model of yeast cell-cycle regulation based on a standard component modeling strategy for protein regulatory networks. PLoS One 11 (5): e0153738.
[Abstract] [Article]

Adames, N.R., Schuck, P.L., Chen, K.C., Murali, T.M., Tyson, J.J., and Peccoud, J. (2015). Experimental testing of a new integrated model of the budding yeast Start transition. Mol. Biol. Cell 26:3966-3984.
[Abstract] [Article]

Kraikivski, P., Chen, K.C., Laomettachit, T., Murali, T.M., and Tyson, J.J. (2015). From START to FINISH: computational analysis of cell cycle control in budding yeast. NPJ Syst. Biol. Appl. 1: 15016.
[Abstract] [Article]

Poirel, C.L., Rodrigues, R.R., Chen, K.C., Tyson, J.J., and Murali, T.M. (2013). Top-down network analysis to drive bottom-up modeling of physiological processes. J Comput Biol 20: 409-418.
[Abstract] [Article]

Tibbles, K.L., Sarkar, S., Novak, B., and Arumugam, P. (2013). CDK-Dependent nuclear localization of B-cyclin Clb1 promotes FEAR activation during meiosis I in budding yeast. PLoS One 8:e79001.
[Abstract] [Article]

Vinod, P.K., Zhou, X., Zhang, T., Mayer, T.U., and Novak, B. (2013). The role of APC/C inhibitor Emi2/Erp1 in oscillatory dynamics of early embryonic cell cycles. Biophys. Chem. 177-178:1-6.
[Abstract] [Article]

Hancioglu, B., and Tyson, J. J. (2012). A mathematical model of mitotic exit in budding yeast: the role of Polo kinase. PLoS One 7:e30810.
[Abstract] [Article]

Ball, D.A., Marehand, J., Poulet, M., Baumann, W.T., Chen, K.C., Tyson, J.J., and Peccoud, J. (2011). Oscillatory dynamics of cell cycle proteins in single yeast cells analyzed by imaging cytometry. PLoS ONE 5, e26272.
[Abstract] [Article]

Zhang, T., Schmierer, B., and Novak, B. (2011). Cell cycle commitment in budding yeast emerges from the cooperation of multiple bi-stable switches. Open Biol. 1:110009
[Abstract] [Article]

Toth, A., Queralt, E., Uhlmann, F., and Novak, B. (2007). Mitotic exit in two dimensions. J Theor Biol 248:560-573
[Abstract] [Article]

Lovrics, A., Csikasz-Nagy, A., Zsely, I., Zador, J., Turanyi, T. and Novak, B. (2006). Time scale and dimension analyses of a budding yeast cell cycle model. BMC Bioinformatics 7:494.
[Abstract] [Article]

Queralt, E., Lehane, C., Novak, B. and Uhlmann, F. (2006). Downregulation of PP2ACdc55 phosphatase by separase initiates mitotic exit in budding yeast. Cell 125:1-14.
[Abstract] [Article]

Cross, F.R., Schroeder, L., Kruse, M. and Chen, K.C. (2005). Quantitative characterization of a mitotic cyclin threshold regulating exit from mitosis. Mol. Biol. Cell 16:2129-2138.
[Abstract] [Article]

Battogtokh, D. and Tyson, J. J. (2004). Bifurcation analysis of a model of the budding yeast cell cycle. Chaos 14:653-661.
[Abstract] [Article]

Chen, K.C., Calzone, L., Csikasz-Nagy, A., Cross, F.R., Novak, B. and Tyson, J.J. (2004). Integrative analysis of cell cycle control in budding yeast. Mol. Biol. Cell 15:3841-3862.
[Abstract] [Article]

Thornton, B. R., Chen, K.C., Cross, F.R., Tyson, J.J., and Toczyski, D.P. (2004). Cycling without the cyclosome: modeling a yeast strain lacking the APC. Cell Cycle 3: 629-633.
[Abstract] [Article]

Ciliberto, A., Novak, B. and Tyson J.J. (2003). Mathematical model of the morphogenesis checkpoint in budding yeast. J. Cell Biol. 163:1243-1254.
[Abstract] [Article]

Chen, K.C., Csikasz-Nagy, A., Gyorffy, B., Val, J., Novak, B. and Tyson, J.J. (2000). Kinetic analysis of a molecular model of the budding yeast cell cycle. Mol. Biol. Cell 11:369-391.
[Abstract] [Article]

Li, F., Subramanian, K., Chen, M. Tyson, J. J. and Cao, Y. (2016). A stochastic spatiotemporal model of a response-reglator network in the Caulobacter crescentus life cycle. Phys. Biol. 13:035007.
[Abstract] [Article]

Subramanian, K., Paul, M.R., and Tyson, J.J. (2015). A theoretical investigation of alternative models. PLoS Comput. Biol. 11: e1004348.
[Abstract] [Article]

Subramanian, K., Paul, M.R., and Tyson, J.J. (2014). De novo production of Turing activator generates polarity in pattern formation. Paper presented at: Advances in Systems and Synthetic Biology (Evry, France), pp. 131-142.
[Abstract] [Article]

Subramanian, K., Paul, M.R., and Tyson, J.J. (2013). Potential role of a bistable histidine kinase switch in the asymmetric division cycle of Caulobacter crescentus. PLoS Comput Biol 9:e1003221.
[Abstract] [Article]

Li, S., Brazhnik, P., Sobral, B., and Tyson, J.J. (2009). Temporal controls of the asymmetric cell division cycle in Caulobacter crescentus. PLoS Comput Biol 5: e1000463.
[Abstract] [Article]

Li, S., Brazhnik, P., Sorbal, B., and Tyson, J.J. (2008). A quantitative study of the division cycle of Caulobacter crescentus stalked cells. PLoS Comput. Biol 4:e9.
[Abstract] [Article]

Brazhnik, P. and Tyson, J. J. (2006). Cell cycle control in bacteria and yeast: a case of convergent evolution? Cell Cycle 5:522-529.
[Abstract] [Article]

Gotoh, T., Kim, J. K., Liu, J., Vila-Caballer, M., Stauffer, P. E., Tyson, J. J. and Finkielstein, C. V. (2016) Model-driven experimental approach reveals the complex regulatory of p53 by the circadian factor Period 2. Proc. Natl. Acad. Sci. 113:13516-13521.
[Abstract] [Article]

Hong, C. I., Conrad, E. D. and Tyson, J. J. (2007). A proposal for robust temperature compensation of circadian rhythms. Proc. Natl. Acad. Sci. U.S.A. 104:1195-1200.
[Abstract] [Article]

Tyson, J.J., Hong, C.I., Thron, C.D.and Novak, B. (1999). A simple model of circadian rhythms based on dimerization and proteolysis of PER and TIM. Biophys. J. 77:2411-2417.
[Abstract] [Article]

Hong, C. I. and Tyson, J. J. (1997). A proposal for temperature compensation of the circadian rhythm in Drosophila based on dimerization of the per protein. Chronobiol. Int. 14:521-529.
[Abstract] [Article]

Calzone, L., Thieffry, D., Tyson, J. J., and Novak, B. (2007). Dynamical modeling of syncytial mitotic cycles in Drosophila embryos. Mol. Syst. Biol. 3:131-141.
[Abstract] [Article]

Novak, B. (2013). Pom1 is not a size ruler. Cell Cycle 12:3463-3464.
[Abstract] [Article]

Cerone, L., Novak, B., and Neufeld, Z. (2012). Mathematical model for growth regulation of fission yeast Schizosaccharomyces pombe. PLoS One 7: e49675.
[Abstract] [Article]

Csikasz-Nagy, A., Gyorffy, B., Alt, W., Tyson, J.J., and Novak, B. (2008). Spatial controls for growth zone formation during the fission yeast cell cycle. Yeast 25:59-69.
[Abstract] [Article]

Castagnetti, S., Novak, B., and Nurse, P. (2007). Microtubules offset growth site from the cell centre in fission yeast. J Cell Sci 120:2205-2213.
[Abstract] [Article]

Csikasz-Nagy, A., Kapuy, O., Gyorffy, B., Tyson, J. J., and Novak, B. (2007). Modeling the septation initiation network (SIN) in fission yeast cells. Curr. Genet. 51:245-255.
[Abstract] [Article]

Sveiczer, A., Tyson, J.J. and Novak, B. (2004). Modelling the fission yeast cell cycle. Brief. Funct. Genomics Proteomics 2:298-307.
[Abstract] [Article]

Novak, B., Pataki, Z., Ciliberto, A. and Tyson, J.J. (2001). Mathematical model of the cell division cycle of fission yeast. Chaos 11:277-286.
[Abstract] [Article]

Sveiczer, A., Tyson, J.J. and Novak, B. (2001). A stochastic molecular model of the fission yeast cell cycle: role of the nucleocytoplasmic ratio in cycle time regulation. Biophys. Chem. 92:1-15.
[Abstract] [Article]

Sveiczer, A., Csikasz-Nagy, A., Gyorffy, B., Tyson, J.J. and Novak, B. (2000). Modeling the fission yeast cell cycle: quantized cycle times in wee1-cdc25∆ mutant cells. Proc. Natl. Acad. Sci. USA 97:7865-7870.
[Abstract] [Article]

Sveiczer, A., Novak, B. and Mitchison, J.M. (1999). Mitotic control in the absence of cdc25 mitotic inducer in fission yeast. J. Cell Sci. 112:1085-1092.
[Abstract] [Article]

Mitchison, J.M., Sveiczer, A. and Novak, B. (1998). Length growth in fission yeast: is growth exponential?--No. Microbiology 144:265-266.
[Abstract] [Article]

Novak, B., Csikasz-Nagy, A., Gyorffy, B., Chen, K. and Tyson, J.J. (1998). Mathematical model of the fission yeast cell cycle with checkpoint controls at the G1/S, G2/M and metaphase/anaphase transitions Biophys. Chem. 72:185-200.
[Abstract] [Article]

Mitchison, J.M., Novak, B. and Sveiczer, A. (1997). Size control in the cell cycle. Cell Biol. Int. 21:461-463
[Abstract] [Article]

Novak, B. and Tyson, J.J. (1997). Modeling the control of DNA replication in fission yeast. Proc. Natl. Acad. Sci. USA 94:9147-9152.
[Abstract] [Article]

Sveiczer, A., Novak, B. and Mitchison, J.M. (1996). The size control of fission yeast revisited. J. Cell Sci. 109:2947-2957.
[Abstract] [Article]

Novak, B. and Tyson, J.J. (1995). Quantitative analysis of a molecular model of mitotic control in fission yeast. J. Theor. Biol. 173:283-305.
[Abstract] [Article]

Novak, B., Sveiczer, A., and Mitchison, J.M. (1993). CO2 production in cell-free extracts of fission yeast detects cell cycle changes. J. Cell Sci. 105:529-531.
[Abstract] [Article]

Mitchison, J.M., Creanor, J. and Novak, B. (1991). Coordation of growth and division during the cell cycle of fission yeast. In The Cell Cycle, D. Beach, B. Stillman, and J. D. Watson, eds. (Cold Spring Harbor, Cold Spring Harbor Laboratory Press), pp. 557-565.
[Abstract] [Article]

Battogtokh, D., and Tyson, J. J. (2016) A bistable switch mechanism for stem cell domain nucleation in the shoot apical meristem. Front. Plant Sci. 7:674.
[Abstract] [Article]

Battogtokh, D., and Tyson, J. J. (2016). A bistable switch mechanism for stem cell domain nucleation in the shoot apical meristem. Front. Plant Sci. 7:674.
[Abstract] [Article]

Zachariae, W., and Tyson, J. J. (2016) Cell division: flipping the mitotic switches. Curr. Biol. 26:R1272-R1274.
[Abstract] [Article]

Gerard, C., Tyson, J.J., Coudreuse, D. and Novak, B. (2015). Cell cycle control by a minimal cdk network. PLoS Comput. Biol. 11:e1004056.
[Abstract] [Article]

Schaap, P., Barrantes, I., Minx, P., Sasaki, N., Anderson, R.W., Bénard, M., Biggar, K.K., Buchler, N.E., Bundschuh, R., Chen, X., et al. (2015). The Physarum polycephalum genome reveals extensive use of prokaryotic two-component and metazoan-type tyrosine kinase signaling. Genome Biol. Evol. Epub ahead of print, PMID 26615215.
[Abstract] [Article]

Tyson, J.J., and Novak, B. (2015). Models in biology: lessons from modeling regulation of the eukaryotic cell cycle. BMC Biol. 13: 46.
[Abstract] [Article]

Tyson, J.J., and Novak, B. (2014). Control of cell growth, division and death: information processing in living cells. Interface Focus 4, 20130070.
[Abstract] [Article]

Gerald, C., Tyson, J.J., and Novak, B. (2013). Minimal models for cell cycle control based on competitive inhibition and multistate phosphorylations of Cdk substrates. Biophys J:104, 1367-1379.
[Abstract] [Article]

Verdugo, A., Vinod, P.K., Tyson, J.J., and Novak, B. (2013). Moleclar mechanisms creating bi-stable switches at cell cycle transitions. Open Biol 3: 120179.
[Abstract] [Article]

Tyson, J.J., and Novak, B., eds. (2012). Irreversible transitions, bistability and checkpoint controls in the eukaryotic cell cycle: a systems-level understanding (San Diego, CA, Elsevier).
[Abstract] [Article]

He, E., Kapuy, O., Oliveira, R.A., Uhlmann, F., Tyson, J.J., and Novak, B. (2011). System -level feedbacks make the anaphase switch irreversible. Proc Natl Acad Sci U S A 108, May 26 [Eprint ahead of print]
[Abstract] [Article]

Tyson, J.J., and Novak, B. (2011). Cell cycle: who turns the crank? Curr. Biol. 21:R185-187.
[Abstract] [Article]

Novak, B., Kapuy, O., Domingo-Sananes, M.R., and Tyson, J.J. (2010). Regulated protein kinases and phosphatases in cell cycle decisions. Curr. Opin. Cell Biol. 22:1-8.
[Abstract] [Article]

Tyson, J.J., and Novak, B. (2010). Functional motifs in biochemical reaction networks. Annu. Rev. Phys. Chem.. 61:219-240.
[Abstract] [Article]

Csikasz-Nagy, A., Kapuy, O., Toth, A., Pal, C., Jensen, L.J., Uhlmann, F., Tyson, J.J., and Novak, B. (2009). Cell cycle regulation by feed-forward loops coupling transcription and phosphorylation. Mol. Syst. Biol. 5:236.
[Abstract] [Article]

Kapuy, O., Barik, D., Domingo Sananes, M.R., Tyson, J.J., and Novak, B. (2009). Bistability by multiple phosphorylation of regulatory proteins. Prog Biophys Mol Biol 100:47-56.
[Abstract] [Article]

Kapuy, O., He, E., Lopez-Avilies, S., Uhlmann, F., Tyson, J.J., and Novak, B. (2009). System-level feedbacks control cell cycle progression FEBS Lett 583:3992-3998.
[Abstract] [Article]

Lopez-Aviles, S., Kapuy, O., Novak, B., and Uhlmann, F. (2009). Irreversibility of mitotic exit is the consequence of systems-level feedback. Nature 459:592-595.
[Abstract] [Article]

Tyson, J.J. (2009). In their own words: interviews with cell cycle. John Tyson on his highly cited paper. Cell Cycle 8: 3261.
[Abstract] [Article]

Csikasz-Nagy, A., Novak, B., and Tyson, J.J. (2008). Reverse engineering models of cell cycle regulation. Adv. Exp. Med. Biol. 641:88-97.
[Abstract] [Article]

Novak, B., and Tyson, J.J. (2008). Design principles of biochemical oscillators. Nature Rev. Mol. Cell Biol. 9:981-991
[Abstract] [Article]

Sabouri-Ghomi, M., Ciliberto, A., Kar, S., Novak, B., and Tyson, J.J. (2008). Antagonism and bistability in protein interaction networks. J Theor Biol. 250:209-218
[Abstract] [Article]

Tyson, J.J., and Novak, B. (2008). Temporal organization of the cell cycle. Curr. Biol. 18: R759-R768.
[Abstract] [Article]

Tyson, J.J., Albert, R., Goldbeter, A., Ruoff, P., and Sible, J.C. (2008). Biological switches and clocks. J. R. Soc. Interface Aug 6; 5 Suppl. 1, S1-S8.
[Abstract] [Article]

Ciliberto, A., Capuani, F., and Tyson, J. J. (2007). Modeling networks of coupled enzymatic reactions using the total quasi-steady state approximation. PLoS Comput Biol 3:e45.
[Abstract] [Article]

Novak, B., Tyson, J. J., Gyorffy, B., and Csikasz-Nagy, A. (2007). Irreversible cell-cycle transitions are due to systems-level feedback. Nature Cell Biol 9:724-728.
[Abstract] [Article]

Sible, J. C. and Tyson, J. J. (2007). Mathematical modeling as a tool for investigating cell cycle control networks. Methods 41:238-247.
[Abstract] [Article]

Tyson, J. J. (2007). Bringing cartoons to life. Nature 445:823.
[Abstract] [Article]

Battogtokh, D. and Tyson, J. J. (2006) Periodic forcing of a mathematical model of the eukaryotic cell cycle. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 73:011910
[Abstract] [Article]

Battogtokh, D., Aihara, K. and Tyson, J. J. (2006). Synchronization of eukaryotic cells by periodic forcing. Phys. Rev. Lett. 96:148102.
[Abstract] [Article]

Conrad, E. D. and Tyson, J. J. (2006). Modeling molecular interaction networks with nonlinear ordinary differential equations. In System Modeling in Cell Biology from Concepts to Nuts and Bolts, Z. Szallasi, J. Stelling, and V. Periwal, eds. (Cambridge, MA: MIT Press), pp. 97-123.
[Abstract] [Article]

Csikasz-Nagy, A., Battogtokh, D., Chen, K. C., Novak, B. and Tyson, J. J. (2006). Analysis of a generic model of eukaryotic cell cycle regulation. Biophys. J. 90:4361-4379.
[Abstract] [Article]

Novak, B., Chen, K.C. and Tyson, J.J. (2005). Systems biology of the yeast cell cycle engine. In Topics in Current Genetics, Vol. 13. Systems Biology: Definitions and Perspectives. L. Alberghina and H. V. Westerhoff eds. (Springer, Berlin /Heidelberg) pp. 305-324.
[Abstract] [Article]

Tyson, J. J. (2005). The coordination of cell growth and division-intentional or incidental? BioEssays 2:72-77.
[Abstract] [Article]

Battogtokh, D. and Tyson, J. J. (2004). Turbulence near cyclic fold bifurcations in birhythmic media. Phys. Rev. E 70:026212.
[Abstract] [Article]

Tyson, J. J. (2004). A precarious balance. Curr. Biol. 14:R262-263.
[Abstract] [Article]

Novak, B. and Tyson, J.J. (2003). Modelling the controls of the eukaryotic cell cycle. Biochem. Soc. Trans. 31:1526-1529.
[Abstract] [Article]

Tyson, J.J., Chen, K.C. and Novak, B. (2003). Sniffers, buzzers, toggles and blinkers: dynamics of regulatory and signaling pathways in the cell. Curr. Opin. Cell Biol. 15:221-231.
[Abstract] [Article]

Fall, C.P., Marland, E.S., Wagner, J. M. and Tyson, J.J. (2002). Computational Cell Biology. (New York, Springer-Verlag).
[Abstract] [Article]

Novak, B., Sible, J.C.and Tyson, J.J. (2002). Checkpoints in the cell cycle. Encyclopedia of Life Sciences. London: Nature Publishing Group. http://www.els.net/   [doi:10.1038/npg.els.0001355], pp.1-8.
[Abstract] [Article]

Tyson J.J., Csikasz-Nagy, A. and Novak, B. (2002). The dynamics of cell cycle regulation. Bioessays 24:1095-1109.
[Abstract] [Article]

Tyson, J.J., Chen, K. and Novak, B. (2001). Network dynamics and cell physiology. Nat. Rev. Mol. Cell Biol. 2:908-916.
[Abstract] [Article]

Tyson, J.J. and Novak, B. (2001). Regulation of the eukaryotic cell cycle: molecular antagonism, hysteresis and irreversible transitions. J. Theor. Biol. 210:249-263.
[Abstract] [Article]

Tyson, J.J., Borisuk, M.T., Chen, K., and Novak, B. (2000). Analysis of complex dynamics in cell cycle regulation, in Computational Modeling of Genetic and Biochemical Networks, (J.M. Bower, and H. Bolouri,Eds), pp. 287-305 (Cambridge, MA, MIT Press).
[Abstract] [Article]

Novak, B., Toth, A., Csikasz-Nagy, A., Gyorffy, B., Tyson, J.J. and Nasmyth, K. (1999). Finishing the cell cycle. J. Theor. Biol. 199:223-233.
[Abstract] [Article]

Novak, B., Csikasz-Nagy, A., Gyorffy, B., Nasmyth, K.and Tyson, J J. (1998). Model scenarios for evolution of the eukaryotic cell cycle. Phil. Trans. R. Soc. Lond. B 353:2063-2076.
[Abstract] [Article]

Tyson, J.J., Chen, K.C. and Novak, B. (1997). The eukaryotic cell cycle: molecules, mechanisms and mathematical models, in Case Studies in Mathematical Modeling: Ecology, Physiology and Cell Biology. (H. G. Othmer, F. R. Adler, M. A. Lewis and J. C. Dallon Eds.) pp. 127-147 (Prentice Hall, Upper Saddle River).
[Abstract] [Article]

Tyson, J.J., Novak, B., Odell, G.M., Chen, K. and Thron, C.D. (1996). Chemical kinetic theory: understanding cell-cycle regulation. Trends Biochem. Sci. 21:89-96.
[Abstract] [Article]

Novak, B. and Tyson, J.J. (1995). Mathematical modeling of the cell division cycle," in Mathematical Population Dynamics: Analysis of Heterogeneity (O. Arino, D. Axelrod & M. Kimmel, Eds.) Vol. 2, pp. 155-169 (Wuerz Publ., Winnipeg).
[Abstract] [Article]

Tyson, J. J., Novak, B., Chen, K. and Val, J. (1995). Checkpoints in the cell cycle from a modeler's perspective. Prog. Cell Cycle Res.1:1-8.
[Abstract] [Article]

Novak, B. and Tyson, J.J. (1993). Modeling the cell division cycle: M-phase trigger, oscillations and size control. J. Theor. Biol. 165:101-134.
[Abstract] [Article]

Tyson, J.J. (1991). Modeling the cell division cycle: cdc2 and cyclin interactions.Proc. Natl. Acad. Sci. USA 88:7328-7332.
[Abstract] [Article]

Tyson, J.J. (1983). Unstable activator models for size control of the cell cycle. J. Theor. Biol. 104:617-631.
[Abstract] [Article]

Tyson, J. J. and Hannsgen, K. B. (1981). Analysis of a Deterministic/Probabilistic Model of the Cell Division Cycle, in Biomathematics and Cell Kinetics (M. Rotenberg, Ed.) pp. 167-176 (Elsevier/North Holland, Amsterdam).
[Abstract] [Article]

Oguz, C., Watson, L.T., Baumann, W. T., and Tyson, J. J. (2017). Predicting network modules of cell cycle regulators using relative protein abundance statistics. BMC Syst. Biol. 11:30
[Abstract] [Article]

Palmisano, A., Hoops, S., Watson, L.T., Jones Jr., T.C., Tyson, J.J., and Shaffer, C.A. (2015). JigCell run manager (JC-RM): a tool for managing large sets of biochenical model parametrizations. BMC Syst. Biol. 9: 95.
[Abstract] [Article]

Palmisano, A., Hoops, S., Watson, L.T., Jones, T.C., Jr., Tyson, J.J., and Shaffer, C.A. (2014). Multisite Model Builder (MSMB): a flexible editor for compact biochemical models. BMC Syst Biol 8:42 [Epub ahead of print].
[Abstract] [Article]

Oguz, C., Teeraphan, L., Chen, K.C., Watson, L.T., Baumann, W.T., and Tyson, J.J. (2013). Optimization and model reduction in the high dimensional parameter space of a budding yeast cell cycle model. BMC Systems Biology 7:53.
[Abstract] [Article]

Randhawa, R., Shaffer, C.A., and Tyson, J.J. (2008). Model composition for macromolecular regulatory networks. IEEE/ACM Trans. Comput. Biol. Bioinform.7:278-287.
[Abstract] [Article]

Randhawa, R., Shaffer, C.A., and Tyson, J.J. (2009). Model aggregation: a building-block approach to creating large macromolecular regulatory networks. Bioinformatics, 15:3289-3295.
[Abstract] [Article]

Shaffer, C.A., Zwolak, J.W., Randhawa, R., and Tyson, J.J. (2009). Modeling molecular regulatory networks with JigCell and PET. Methods Mol. Biol. Syst. Biol. 500: 81-111.
[Abstract] [Article]

Panning, T.D., Watson, L.T., Allen, N.A., Chen, K.C., Shaffer, C.A., and Tyson, J.J. (2008). Deterministic parallel global parameter estimation for a model of the budding yeast cell cycle. J Glob Optim 40:719-738.
[Abstract] [Article]

Panning, T.D., Watson, L.T., Shaffer, C.A., and Tyson, J.J. (2007). A mathematical programming formulation for the budding yeast cell cycle. Simulation 8:497-514.
[Abstract] [Article]

Allen, N. A., Chen, K. C., Shaffer, C. A., Tyson, J. J. and Watson, L. T. (2006). Computer evaluation of network dynamics models with application to cell cycle control in budding yeast. IEE Proc Syst Biol (Stevenage) 153:13-21.
[Abstract] [Article]

Vass, M. T., Shaffer, C. A., Ramakrishnan, N., Watson, L. T. and Tyson, J. J. (2006). The JigCell model builder: a spreadsheet interface for creating biomedical reaction network models. IEEE/ACM Trans Comput Biol Bioinform 3:155-164.
[Abstract] [Article]

Zwolak, J.W., Tyson, J.J. and Watson, L.T. (2005). Parameter estimation for a mathematical model of the cell cycle in frog eggs. J. Comp. Biol. 12:48-63.
[Abstract] [Article]

Zwolak, J. W., Tyson, J. J. and Watson, L. T. (2005). Globally optimized parameters for a model of mitotic control in frog egg extracts. IEE Syst Biol. (Stevenage) 152:81-92.
[Abstract] [Article]

Vass, M. T., Allen, N. A., Shaffer, C. A., Ramakrishnan, N., Watson, L. T. and Tyson, J. J. (2004). The Jigcell model builder and run manager. Bioinformatics 20:3680-3681.
[Abstract] [Article]

Allen, N.A., Calzone, L., Chen, K.C., Ciliberto, A., Ramakrishnan, N., Shaffer, C.A., Sible, J.C., Tyson, J.J., Vass, M.T., Watson, L.T. and Zwolak, J.W. (2003). Modeling regulatory networks at Virginia Tech. OMICS 7:285-299.
[Abstract] [Article]

Clarke, R., Tyson, J. J. and Dixon, J. M. (2015). Endocrine resistance in breast cancer--an overview and update. Mol. Cell. Endocrinol. 418 (03):220-234.
[Abstract] [Article]

Hong, T., Oguz, C., and Tyson, J.J. (2015). A mathematical framework for understanding four-dimensional heterogeneous differentiation of CD4+ T cells. Bull. Math. Biol. 77 (6): 1046-1064.
[Abstract] [Article]

Tavassoly, I., Parmar, J.H., Shajahan-Haq, A.N., Clarke, R., Baumann, W.T., and Tyson, J.J. (2015). Dynamic modeling of the interaction between autophagy and apoptosis in mammalian cells. CPT Pharmacometrics Syst. Pharmacol. 4 (4): 263-272.
[Abstract] [Article]

Chen, C., Baumann, W.T., Xing, J., Xu, L., Clarke, R., and Tyson, J.J. (2014). Mathematical models of the transitions between endocrine therapy response and resistant states in breast cancer. J Roy Soc Interface 11, 20140206.
[Abstract] [Article]

Chen, C., Baumann, W.T., Clarke, R., and Tyson, J.J. (2013). Modeling the estrogen receptor to growth factor receptor signaling switch in human breast cancer cells. FEBS Lett 587:3327-3334.
[Abstract] [Article]

Parmar, J.H., Cook, K.L., Shajahan, A.N., Clarke, P., Tavassoly, I., Clarke, R., Tyson, J.J., and Baumann, W.T. (2013). Modeling the effect of GRP78 on anti-estrogen sensitivity and resistance in breast cancer. Interface Focus 3:20130012.
[Abstract] [Article]

Tuck, C., Zhang, T., Potapova, T.A., Malumbres, M., and Novak, B. (2013). Robust mitotic entry is ensured by a latching switch. Biol. Open. 2:924-931.
[Abstract] [Article]

Clarke. R., Cook, K.L., Hu, R., Facey, C.O., Tavassoly, I., Schwartz, J.L., Baumann, W.T., Tyson, J.J., Xuan, J., Wang, Y., Wärri, A., and Shajahan, A.N. (2012). Endoplastic reticulum stress, the unfolded protein response, autophagy and the integrated regulation of breast cancer cell fate. Cancer Res. 72:1321-1331.
[Abstract] [Article]

Fu, Y., Glaros, T., Zhu, M., Wang, P., Wu, Z., Tyson, J.J., Li, L,, and Xing, J. (2102). Network topologies and dynamics leading to endotoxin tolerance and priming in innate immune cells. PLoS Comput. Biol. 8:e1002526.
[Abstract] [Article]

Hong, T., Xing, J., Li, L., and Tyson, J.J. (2012). A simple theoretical framework for understanding heterogeneous differentiation of CD4+ T cells. BMC Syst. Biol. 6:66.
[Abstract] [Article]

Clarke, R., Shajahan, A.N., Wang, Y., Tyson, J.J., Riggins, R.B., Weiner, L.M., Baumann, W.T., Xuan, J., Zhang, B., Facey, C.,Aiyer, H., Cook, K., Hickman, F. E.,Tavassoly, I., Verdugo, A., Chen, C., Zwart, A., Warri, A., and Hilakivi-Clarke, L. A. (2011). Endoplasmic reticulum stress, the unfolded protein response, and gene network modeling in antiestrogen resistant breast cancer. Hormone Mol. Biol. Clin. Invest 5: 35-44.
[Abstract] [Article]

Hong, T., Xing, J., Li, L., and Tyson, J.J. (2011). A mathematical model for the reciprocal differentiation of T helper 17 cells and induced regulatory T cells. PLoS Comput. Bio.l 7: e1002122.
[Abstract] [Article]

Singhania, R., Sramkoski, R.M., Jacobberger, J.W., and Tyson, J.J. (2011). A hybrid model of mammalian cell cycle regulation. PLoS Comput Biol 7: e1001077.
[Abstract] [Article]

Tyson, J.J., Baumann, W.T., Chen, C., Verdugo, A., Tavassoly, I., Wang, Y., Weiner, L.M., and Clarke, R. (2011). Dynamic modelling of eostrogen signalling and cell fate in breast cancer cells. Nat. Rev. Cancer 11: 523-532.
[Abstract] [Article]

Conradie, R., Bruggeman, F.J., Ciliberto, A., Csikasz-Nagy, A., Novak, B., Westerhof, H.V., and Snoep, J.L. (2010). Restriction point control of the mammalian cell cycle via the cyclin E/Cdk2:p27 complex. FEBS J:277 357-367.
[Abstract] [Article]

McGuinness, B.E., Anger, M., Kouznetsova, A., Gil-Bernabe, A.M., Helmhart, W., Kudo, N.R., Wuensche, A., Taylor, S., Hoog, C., Novak, B., and Nasmyth, K. (2009). Regulation of APC/C activity in oocytes by a Bub1-dependent spindle assembly checkpoint. Curr. Biol. 19: 369-380.
[Abstract] [Article]

Su, J., Zhang, T., Tyson, J.J., and Li, L. (2009). The interleukin-1 receptor associated kinase M selectively inhibits the alternative, instead of the classical NFkappaB pathway. J. Innate Immun. 1: 164-174.
[Abstract] [Article]

Zhang, T., Brazhnik, P., and Tyson, J.J. (2009). Computational analysis of dynamical responses to the intrinsic pathway of programmed cell death. Biophys J. 97: 415-432.
[Abstract] [Article]

Zhang, T., Brazhnik, P. and Tyson, J. J. (2007). Exploring mechanisms of the DNA-damage response: p53 pulses and their possible relevance to apoptosis. Cell Cycle 6:85-94.
[Abstract] [Article]

Tyson, J.J. (2006). Another turn for p53. Mol. Syst. Biol. 2:2006.0032.
[Abstract] [Article]

Ciliberto, A., Novak, B. and Tyson, J. J. (2005). Steady states and oscillations in the p53/Mdm2 network. Cell Cycle 4:488-493.
[Abstract] [Article]

Novak, B. and Tyson, J. J. (2004). A model for restriction point control of the mammalian cell cycle. J. Theor. Biol. 230:563-579.
[Abstract] [Article]

Tyson, J.J. (2004). Monitoring p53's pulse. Nat. Genet. 36:113-114.
[Abstract] [Article]

Ciliberto, A. and Tyson, J.J. (2000). Mathematical model for early development of the sea urchin embryo, Bull. Math. Biol. 62:37-59.
[Abstract] [Article]

Barik, D., Ball, D. A., Peccoud, J. and Tyson, J. J. (2016). A stochastic model of the yeast cell cycle reveals roles for feedback regulation in limiting cell viability. PLoS Comput. Biol. 12:e1005230.
[Abstract] [Article]

Laomettachit, T., Chen, K.C., Baumann, W.T., and Tyson, J.J. (2016). A model of yeast cell-cycle regulation based on a standard component modeling strategy for protein regulatory networks. PLoS One 11 (5): e0153738.
[Abstract] [Article]

Oguz, C., Palmisano, A., Laomettachit, T., Watson, L.T., Baumann, W.T., and Tyson, J.J. (2014). A stochastic model correctly predicts changes in budding yeast cell cycle dynamics upon periodic expression of CLN2. PLoS One 9(5):e96726.
[Abstract] [Article]

Ball, D.A., Adames, N.R., Reischmann, N., Barik, D., Franck, C.T., Tyson, J.J., and Peccoud, J. (2013). Measurement and modeling of transcriptional noise in the cell cycle regulatory network. Cell Cycle 12: 3203-3218.
[Abstract] [Article]

Liu, Z., Pu, Y., Li, F., Shaffer, C.A., Hoops, S., Tyson, J.J., and Cao, Y. (2012). Hybrid modeling and simulation of stochastic effects on progression through the eukaryotic cell cycle. J Chem Phys 136:034105.
[Abstract] [Article]

Ball, D.A., Ahn, T.-H., Wang, P., Chen, K.C., Cao, Y., Tyson, J.J., Peccoud, J., and Baumann, W.T. (2011). Stochastic exit from mitosis in budding yeast: model predictions and experimental observations. Cell Cycle 10: 999-1009.
[Abstract] [Article]

Barik, D., Baumann, W.T., Paul, M.R., Novak, B., and Tyson, J.J. (2010). A model of yeast cell cycle regulation based on multisite phosphorylation. Mol. Syst. Biol. 6:405.
[Abstract] [Article]

Kar, S., Baumann, W.T., Paul, M.R., and Tyson, J.J. (2009). Exploring the roles of noise in the eukaryotic cell cycle. Proc. Natl. Acad. Sci. USA 106:6471-6476.
[Abstract] [Article]

Barik, D., Paul, M.R., Baumann, W.T., Cao, Y., and Tyson, J.J. (2008). Stochastic simulation of enzyme-catalyzed reactions with disparate time scales. Biophys. J. 95: 3563-3574.
[Abstract] [Article]

Tyson, J.J., and Novak, B. (2014). Bistability, oscillations, and travelling waves in frog egg extracts. Bull Math Biol Epub ahead of print.
[Abstract] [Article]

Zhang, T., Tyson, J.J., and Novak, B. (2013). Role for regulated phosphatase activity in generating mitotic oscillations in Xenopus cell-free extracts. Proc Natl Acad Sci USA 110: 20539-20544.
[Abstract] [Article]

Zwolak, J.W., Adjerid, N., Bagci, E.Z., Tyson, J.J., and Sible, J.C. (2009). A quantitative model of the effect of unreplicated DNA on cell cycle progression in frog egg extracts. J. Theor. Biol. 260: 110-120.
[Abstract] [Article]

Ciliberto, A., Lukacs, A., Toth, A.,Tyson, J. J. and Novak, B. (2005). Rewiring the exit from mitosis. Cell Cycle 4:1107-1112.
[Abstract] [Article]

Ciliberto, A., Petrus, M.J., Tyson, J.J. and Sible, J.C. (2003). A kinetic model of the cyclin E/Cdk2 developmental timer in Xenopus laevis embryos. Biophys Chem. 104:573-89.
[Abstract] [Article]

Sha, W., Moore, J., Chen, K., Lassaletta, A.D., Yi, C.-S., Tyson, J.J. and Sible, J.C. (2003). Hysteresis drives cell-cycle transitions in Xenopus laevis egg extracts. Proc. Natl. Acad. Sci. USA 100:975-980.
[Abstract] [Article]

Borisuk, M.T. and Tyson, J.J. (1998). Bifurcation analysis of a model of mitotic control in frog eggs. J. Theor. Biol. 195:69-85.
[Abstract] [Article]

Marlovits, G., Tyson, C.J., Novak, B. and Tyson, J.J. (1998). Modeling M-phase control in Xenopus oocyte extracts: the surveillance mechanism for unreplicated DNA. Biophys. Chem. 72:169-184.
[Abstract] [Article]

Novak, B. and Tyson, J.J. (1993). Numerical analysis of a comprehensive model of M-phase control in Xenopus oocyte extracts and intact embryos. J. Cell Sci. 106:1153-1168. Highlighted by News and Views, Nature, 9 June 1994, p. 437.
[Abstract] [Article]