Staff profile

• Systems biology

Chapter in book

• The POLARIS Peptide: Role in Hormone Signalling and Root Growth
  Mehdi, S., Mudge, A., Rowe, J., Liu, J., Topping, J., & Lindsey, K. (2016). The POLARIS Peptide: Role in Hormone Signalling and Root Growth. In A. Huffaker, & G. Pearce (Eds.), Annual Plant Reviews: Peptide Signals in Plants. Wiley
• POLARIS.
  Lindsey, K., Mehdi, S., Casson, S., Mudge, A., Topping, J., & Liu, J. (2013). POLARIS. In A. Kastin (Ed.), The Handbook of Biologically Active Peptides, 2nd Edition (40-45). (2nd.). Academic Press

Journal Article

• Modelling Plant Cell Growth
  Liu, J., Moore, S., & Lindsey, K. (online). Modelling Plant Cell Growth. https://doi.org/10.1002/9780470015902.a0020107.pub2
• Modelling plant hormone gradients
  Moore, S., Zhang, X., Liu, J., & Lindsey, K. (online). Modelling plant hormone gradients. https://doi.org/10.1002/9780470015902.a0023733
• Necessity for modeling hormonal crosstalk in arabidopsis root development?
  Moore, S., Liu, J., Chen, C., & Lindsey, K. (2025). Necessity for modeling hormonal crosstalk in arabidopsis root development?. Trends in Plant Science, 30(5), 484-498. https://doi.org/10.1016/j.tplants.2025.02.009
• A predictive model for ethylene-mediated auxin and cytokinin patterning in the Arabidopsis root
  Moore, S., Jervis, G., Topping, J., Chen, C., Liu, J., & Lindsey, K. (2024). A predictive model for ethylene-mediated auxin and cytokinin patterning in the Arabidopsis root. Plant communications, 5(7), Article 100886. https://doi.org/10.1016/j.xplc.2024.100886
• Putrescine depletion affects Arabidopsis root meristem size by modulating auxin and cytokinin signaling and ROS accumulation
  Hashem, A., Moore, S., Chen, S., Hu, C., Zhao, Q., IE Elasawi, I., Feng, Y., Topping, J., Liu, J., Lindsey, K., & Chen, C. (2021). Putrescine depletion affects Arabidopsis root meristem size by modulating auxin and cytokinin signaling and ROS accumulation. International Journal of Molecular Sciences, 22(8), Article 4094. https://doi.org/10.3390/ijms22084094
• Understanding hormonal crosstalk in Arabidopsis root development via emulation and history matching
  Jackson, S., Vernon, I., Liu, J., & Lindsey, K. (2020). Understanding hormonal crosstalk in Arabidopsis root development via emulation and history matching. Statistical Applications in Genetics and Molecular Biology, 19(2), Article 20180053. https://doi.org/10.1515/sagmb-2018-0053
• Design principles for decoding calcium signals to generate specific gene expression via transcription
  Liu, J., Lenzoni, G., & Knight, M. R. (2020). Design principles for decoding calcium signals to generate specific gene expression via transcription. Plant Physiology, 182(4), 1743-1761. https://doi.org/10.1104/pp.19.01003
• Predicting plant immunity gene expression by identifying the decoding mechanism of calcium signatures
  Lenzoni, G., Liu, J., & Knight, M. (2018). Predicting plant immunity gene expression by identifying the decoding mechanism of calcium signatures. New Phytologist, 217(4), 1598-1609. https://doi.org/10.1111/nph.14924
• Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions
  Vernon, I., Liu, J., Goldstein, M., Rowe, J., Topping, J., & Lindsey, K. (2018). Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions. BMC systems biology, 12, Article 1. https://doi.org/10.1186/s12918-017-0484-3
• Crosstalk complexities between auxin, cytokinin and ethylene in Arabidopsis root development: from experiments to systems modelling, and back again
  Liu, J., Moore, S., Chen, C., & Lindsey, K. (2017). Crosstalk complexities between auxin, cytokinin and ethylene in Arabidopsis root development: from experiments to systems modelling, and back again. Molecular Plant, 10(12), 1480-1496. https://doi.org/10.1016/j.molp.2017.11.002
• A recovery principle provides insight into auxin pattern control in the Arabidopsis root
  Moore, S., Liu, J., Zhang, X., & Lindsey, K. (2017). A recovery principle provides insight into auxin pattern control in the Arabidopsis root. Scientific Reports, 7, Article 43004. https://doi.org/10.1038/srep43004
• Abscisic acid regulates root growth under osmotic stress conditions via an interacting hormonal network with cytokinin, ethylene and auxin
  Rowe, J., Topping, J., Liu, J., & Lindsey, K. (2016). Abscisic acid regulates root growth under osmotic stress conditions via an interacting hormonal network with cytokinin, ethylene and auxin. New Phytologist, 211(1), 225-239. https://doi.org/10.1111/nph.13882
• Some fundamental aspects of modelling auxin patterning in the context of auxin-ethylene-cytokinin crosstalk
  Moore, S., Zhang, X., Liu, J., & Lindsey, K. (2015). Some fundamental aspects of modelling auxin patterning in the context of auxin-ethylene-cytokinin crosstalk. Plant Signaling & Behavior, 10(10), Article e1056424. https://doi.org/10.1080/15592324.2015.1056424
• Combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin-binding transcription activators (CAMTAs) to produce specific gene expression responses
  Liu, J., Whalley, H., & Knight, M. (2015). Combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin-binding transcription activators (CAMTAs) to produce specific gene expression responses. New Phytologist, 208(1), 174-187. https://doi.org/10.1111/nph.13428
• Spatiotemporal modelling of hormonal crosstalk explains the level and patterning of hormones and gene expression in Arabidopsis thaliana wildtype and mutant roots
  Moore, S., Zhang, X., Mudge, A., Rowe, J., Topping, J., Liu, J., & Lindsey, K. (2015). Spatiotemporal modelling of hormonal crosstalk explains the level and patterning of hormones and gene expression in Arabidopsis thaliana wildtype and mutant roots. New Phytologist, 207(4), 1110-1122. https://doi.org/10.1111/nph.13421
• Dissecting the regulation of pollen tube growth by modeling the interplay of hydrodynamics, cell wall and ion dynamics
  Liu, J., & Hussey, P. (2014). Dissecting the regulation of pollen tube growth by modeling the interplay of hydrodynamics, cell wall and ion dynamics. Frontiers in Plant Science, 5, Article 392. https://doi.org/10.3389/fpls.2014.00392
• Hormonal crosstalk for root development: a combined experimental and modeling perspective
  Liu, J., Rowe, J., & Lindsey, K. (2014). Hormonal crosstalk for root development: a combined experimental and modeling perspective. Frontiers in Plant Science, 5, Article 116. https://doi.org/10.3389/fpls.2014.00116
• Elucidating the regulation of complex signalling systems in plant cells
  Liu, J., Lindsey, K., & Hussey, P. J. (2014). Elucidating the regulation of complex signalling systems in plant cells. Biochemical Society Transactions, 42(1), 219-223. https://doi.org/10.1042/bst20130090
• Interaction of PLS and PIN and hormonal crosstalk in Arabidopsis root development
  Liu, J., Mehdi, S., Topping, J., Friml, J., & Lindsey, K. (2013). Interaction of PLS and PIN and hormonal crosstalk in Arabidopsis root development. Frontiers in Plant Science, 4, Article 75. https://doi.org/10.3389/fpls.2013.00075
• Modelling and experimental analysis of the role of interacting cytosolic and vacuolar pools in shaping low temperature calcium signatures in plant cells
  Liu, J., Knight, H., Hurst, C., & Knight, M. (2012). Modelling and experimental analysis of the role of interacting cytosolic and vacuolar pools in shaping low temperature calcium signatures in plant cells. Molecular bioSystems, 2012(8), 2205-2220. https://doi.org/10.1039/c2mb25072a
• Towards the creation of a systems tip growth model for a pollen tube.
  Liu, J., & Hussey, P. (2011). Towards the creation of a systems tip growth model for a pollen tube. Plant Signaling & Behavior, 6(4), 520-522. https://doi.org/10.4161/psb.6.4.14750
• Modelling dynamic plant cells
  Liu, J., Grieson, C. S., Webb, A. A., & Hussey, P. J. (2010). Modelling dynamic plant cells. Current Opinion in Plant Biology, 13(6), 744-749. https://doi.org/10.1016/j.pbi.2010.10.002
• A Compartmental Model Analysis of Integrative and Self-Regulatory Ion Dynamics in Pollen Tube Growth
  Liu, J., Piette, B., Deeks, M., Franklin-Tong, V., & Hussey, P. (2010). A Compartmental Model Analysis of Integrative and Self-Regulatory Ion Dynamics in Pollen Tube Growth. PLoS ONE, 5(10), Article e13157. https://doi.org/10.1371/journal.pone.0013157
• Modelling and experimental analysis of hormonal crosstalk in Arabidopsis
  Liu, J., Mehdi, S., Topping, J., Tarkowski, P., & Lindsey, K. (2010). Modelling and experimental analysis of hormonal crosstalk in Arabidopsis. Molecular Systems Biology, 6(1), Article 373. https://doi.org/10.1038/msb.2010.26
• A Thermodynamic Model of Microtubule Assembly and Disassembly
  Piette, B., Liu, J., Peeters, K., Smertenko, A., Hawkins, T., Deeks, M., Quinlan, R., Zakrzewski, W., & Hussey, P. (2009). A Thermodynamic Model of Microtubule Assembly and Disassembly. PLoS ONE, 4(8), Article e6378. https://doi.org/10.1371/journal.pone.0006378
• A kinetic model for the metabolism of the herbicide safener fenclorim in Arabidopsis thaliana.
  Liu, J., Brazier-Hicks, M., & Edwards, R. (2009). A kinetic model for the metabolism of the herbicide safener fenclorim in Arabidopsis thaliana. Biophysical Chemistry, 143(1-2), 85-94. https://doi.org/10.1016/j.bpc.2009.04.006
• Determination of metabolic fluxes in a non-steady-state system
  Baxter, C., Liu, J., Fernie, A., & Sweetlove, L. (2007). Determination of metabolic fluxes in a non-steady-state system. Phytochemistry, 68(16-18), 2313-2319
• The metabolic response of heterotrophic Arabidopsis cells to oxidative stress
  Baxter, C., Redestig, H., Schauer, N., Repsilber, D., Patil, K., Nielsen, J., Selbig, J., Liu, J., Fernie, A., & Sweetlove, L. (2007). The metabolic response of heterotrophic Arabidopsis cells to oxidative stress. Plant Physiology, 143(1), 312-325
• Dissipation and maintenance of stable states in an enzymatic system: Analysis and simulation
  Liu, J. (2006). Dissipation and maintenance of stable states in an enzymatic system: Analysis and simulation. Biophysical Chemistry, 120(3), 207-214. https://doi.org/10.1016/j.bpc.2005.11.011
• Collapse of single stable states via a fractal attraction basin: Analysis of a representative metabolic network
  Liu, J., Crawford, J., & Leontiou, K. (2005). Collapse of single stable states via a fractal attraction basin: Analysis of a representative metabolic network. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 461(2060), 2327-2338. https://doi.org/10.1098/rspa.2004.1436
• Kinetic constraints for formation of steady states in biochemical networks
  Liu, J. (2005). Kinetic constraints for formation of steady states in biochemical networks. Biophysical Journal, 88(5), 3212-3223. https://doi.org/10.1529/biophysj.104.056085
• Effects of periodic input on the quasi-steady state assumptions for enzyme-catalysed reactions
  Stoleriu, I., Davidson, F., & Liu, J. (2005). Effects of periodic input on the quasi-steady state assumptions for enzyme-catalysed reactions. Journal of Mathematical Biology, 50(2), 115-132
• Kinetics of labelling of organic and amino acids in potato tubers by gas chromatography-mass spectrometry following incubation in 13C labelled isotopes
  Roessner-Tunali, U., Liu, J., Leisse, A., Balbo, I., Perez-Melis, A., Willmitzer, L., & Fernie, A. (2004). Kinetics of labelling of organic and amino acids in potato tubers by gas chromatography-mass spectrometry following incubation in 13C labelled isotopes. The Plant Journal, 39(4), 668-679. https://doi.org/10.1111/j.1365-313x.2004.02157.x
• Quasi-steady state assumptions for non-isolated enzyme-catalysed reactions
  Stoleriu, I., Davidson, F., & Liu, J. (2004). Quasi-steady state assumptions for non-isolated enzyme-catalysed reactions. Journal of Mathematical Biology, 48(1), 82-104
• Sufficient conditions for coordination of coupled nonlinear biochemicalsystems: Analysis of a simple, representative example
  Liu, J., & Marshall, D. (2003). Sufficient conditions for coordination of coupled nonlinear biochemicalsystems: Analysis of a simple, representative example. Journal of Biological Systems, 11(3), 275-291
• Spatial heterogeneity and the stability of reaction states inautocatalysis
  Marion, G., Mao, X., Renshaw, E., & Liu, J. (2002). Spatial heterogeneity and the stability of reaction states inautocatalysis. Physical review E: Statistical physics, plasmas, fluids, and related interdisciplinary topics, 66(5),
• Global stability of the attracting set of an enzyme-catalysed reactionsystem
  Davidson, F., & Liu, J. (2002). Global stability of the attracting set of an enzyme-catalysed reactionsystem. Mathematical and computer modelling, 35(13), 1467-1481
• Existence and uniqueness of limit cycles in an enzyme-catalysedreaction system
  Davidson, F., Xu, R., & Liu, J. (2002). Existence and uniqueness of limit cycles in an enzyme-catalysedreaction system. Applied Mathematics and Computation, 127(2-3), 165-179
• State selection in coupled identical biochemical systems withcoexisting stable states
  Liu, J. (2002). State selection in coupled identical biochemical systems withcoexisting stable states. BioSystems, 65(1), 49-60. https://doi.org/10.1016/s0303-2647%2802%2900003-5
• C-13-NMR analysis of glucose metabolism during citric acid productionby Aspergillus niger
  Peksel, A., Torres, N., Liu, J., Juneau, G., & Kubicek, C. (2002). C-13-NMR analysis of glucose metabolism during citric acid productionby Aspergillus niger. Applied Microbiology and Biotechnology, 58(2), 157-163
• Enhancement and restriction of system coordination by interaction ofpathways
  Liu, J. (2001). Enhancement and restriction of system coordination by interaction ofpathways. Journal of Biological Systems, 9(3), 169-186
• Sufficient conditions for coordination of a forced biochemical systemwith the interplay of activation and inhibition
  Liu, J. (2000). Sufficient conditions for coordination of a forced biochemical systemwith the interplay of activation and inhibition. Journal of Biological Systems, 8(3), 237-253
• Sufficient conditions for coordination of a nonlinear biochemicalsystem under external forcing
  Liu, J., & Crawford, J. (2000). Sufficient conditions for coordination of a nonlinear biochemicalsystem under external forcing. Journal of Physical Chemistry B (Soft Condensed Matter and Biophysical Chemistry), 104(12), 2623-2629
• Dependence of flux distribution and system coordination on dynamicalstates for biochemical systems with multiple coexisting states
  Liu, J. (1999). Dependence of flux distribution and system coordination on dynamicalstates for biochemical systems with multiple coexisting states. Journal of Biological Systems, 7(1), 67-84
• Coordination restriction of enzyme-catalysed reaction systems asnonlinear dynamical systems
  Liu, J. (1999). Coordination restriction of enzyme-catalysed reaction systems asnonlinear dynamical systems. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 455(1981), 285-298
• Stability of an autocatalytic biochemical system in the presence ofnoise perturbations
  Liu, J., & Crawford, J. (1998). Stability of an autocatalytic biochemical system in the presence ofnoise perturbations. IMA journal of mathematics applied in medicine and biology, 15(4), 339-350
• Transitions and new dynamical states induced by noise in a multiplyregulated biochemical system
  Liu, J., & Crawford, J. (1997). Transitions and new dynamical states induced by noise in a multiplyregulated biochemical system. Biophysical Chemistry, 69(2-3), 97-106
• Stability of an autocatalytic system under noise perturbations and itsdependence on the basin of attraction
  Liu, J., & Crawford, J. (1997). Stability of an autocatalytic system under noise perturbations and itsdependence on the basin of attraction. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 453(1961), 1195-1203
• Prospects for advancing the understanding of complex biochemical systems
  Liu, J., Crawford, J., Viola, R., & Goodman, B. (1997). Prospects for advancing the understanding of complex biochemical systems. Plant Molecular Biology, 33(4), 573-581