TY - CHAP A1 - Heiner, Monika A1 - Breitling, Rainer A1 - Donaldson, Robin A1 - Gilbert, David T1 - Biomodel Engineering - From Structure to Behavior T2 - Transactions on Computational Systems Biology XII : Special Issue on Modeling Methodologies Y1 - 2010 SN - 978-3-642-11711-4 SN - 978-3-642-11712-1 U6 - https://doi.org/10.1007/978-3-642-11712-1 SP - 1 EP - 12 PB - Springer CY - Berlin [u.a.] ER - TY - GEN A1 - Pârvu, Ovidiu A1 - Gilbert, David A1 - Heiner, Monika A1 - Liu, Fei A1 - Saunders, Nigel A1 - Shaw, Simon T1 - Spatial-temporal modelling and analysis of bacterial colonies with phase variable genes T2 - ACM Transactions on Modeling and Computer Simulation (TOMACS) Y1 - 2015 UR - http://dl.acm.org/citation.cfm?id=2742546 U6 - https://doi.org/10.1145/2742546 SN - 1558-1195 SN - 1049-3301 VL - 25 IS - 2 SP - 13 ER - TY - GEN A1 - Gilbert, David A1 - Heiner, Monika T1 - Preface Advances in Computational Methods in Systems Biology T2 - Theoretical Computer Science Y1 - 2015 U6 - https://doi.org/doi:10.1016/j.tcs.2015.08.013 SN - 0304-3975 VL - 599 SP - 2 EP - 3 ER - TY - CHAP A1 - Parvu, Ovidiu A1 - Gilbert, David A1 - Heiner, Monika A1 - Liu, Fei A1 - Saunders, Nigel ED - Gupta, Ashutosh ED - Henzinger, Thomas A. T1 - Modelling and Analysis of Phase Variation in Bacterial Colony Growth T2 - Computational Methods in Systems Biology, 11th International Conference, CMSB 2013, Klosterneuburg, Austria, September 22-24, 2013 Y1 - 2013 SN - 978-3-642-40707-9 U6 - https://doi.org/10.1007/978-3-642-40708-6_7 N1 - referiert SP - 78 EP - 91 PB - Springer CY - Berlin [u.a.] ER - TY - CHAP A1 - Gilbert, David A1 - Heiner, Monika A1 - Liu, Fei A1 - Saunders, Nigel T1 - Colouring Space - A Coloured Framework for Spatial Modelling in Systems Biology T2 - Application and Theory of Petri Nets and Concurrency, 34th International Conference, PETRI NETS 2013, Milan, Italy, June 24-28, 2013 Y1 - 2013 UR - http://link.springer.com/chapter/10.1007%2F978-3-642-38697-8_13 N1 - referiert SP - 230 EP - 249 PB - Springer CY - Berlin [u.a.] ER - TY - GEN A1 - Liu, Fei A1 - Heiner, Monika A1 - Gilbert, David T1 - Coloured Petri nets for multilevel, multiscale and multidimensional modelling of biological systems T2 - Briefings in Bioinformatics Y1 - 2019 U6 - https://doi.org/10.1093/bib/bbx150 SN - 1477-4054 SN - 1467-5463 VL - 20 IS - 3 SP - 877 EP - 886 ER - TY - GEN A1 - Gilbert, David A1 - Heiner, Monika A1 - Jayaweera, Yasoda A1 - Rohr, Christian T1 - Towards dynamic genome scale models T2 - Briefings in Bioinformatics Y1 - 2019 U6 - https://doi.org/10.1093/bib/bbx096 SN - 1477-4054 SN - 1467-5463 VL - 20 IS - 4 SP - 1167 EP - 1180 ER - TY - GEN A1 - Gilbert, David A1 - Heiner, Monika A1 - Ghanbar, Leila T1 - Personalised models for human – gut microbiota interaction T2 - PeerJ preprints Y1 - 2017 UR - https://peerj.com/preprints/3267/ U6 - https://doi.org/10.7287/peerj.preprints.3267v1 SN - 2167-9843 VL - 5 IS - e3267v1 ER - TY - GEN A1 - Gilbert, David A1 - Heiner, Monika A1 - Rohr, Christian T1 - Petri-net-based 2D Design of DNA Walker Circuits T2 - Natural Computing Y1 - 2018 U6 - https://doi.org/10.1007/s11047-018-9671-4 SN - 1572-9796 SN - 1567-7818 VL - 17 IS - 1 SP - 161 EP - 182 ER - TY - GEN A1 - Xu, Hongwei A1 - Curtis, Tanya Y. A1 - Powers, Stephen J. A1 - Raffan, Sarah A1 - Gao, Runhong A1 - Huang, Jianhua A1 - Heiner, Monika A1 - Gilbert, David A1 - Halford, Nigel G. T1 - Genomic, biochemical and modelling analyses of asparagine synthetases from wheat T2 - Frontiers in Plant Science Y1 - 2018 U6 - https://doi.org/10.3389/fpls.2017.02237 SN - 1664-462X VL - 8 ER - TY - GEN A1 - Colombo, Riccardo A1 - Damiani, Chiara A1 - Gilbert, David A1 - Heiner, Monika A1 - Mauri, Giancarlo A1 - Pescini, Dario T1 - Emerging ensembles of kinetic parameters to identify experimentally observed phenotypes T2 - BMC bioinformatics KW - Ensembles KW - Fluxes KW - Kinetic parameters KW - Mechanistic simulations KW - Metabolism KW - ODEs KW - Steady state KW - Systems biology Y1 - 2018 UR - https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2181-7 U6 - https://doi.org/10.1186/s12859-018-2181-7 SN - 1471-2105 VL - 19 IS - Suppl. 7 SP - 46 EP - 59 ER - TY - GEN A1 - Liu, Fei A1 - Heiner, Monika A1 - Gilbert, David T1 - Fuzzy Petri nets for modelling of uncertain biological systems T2 - Briefings in Bioinformatics Y1 - 2018 U6 - https://doi.org/10.1093/bib/bby118 SN - 1477-4054 SN - 1467-5463 VL - 2018 ER - TY - CHAP A1 - Self, Timothy A1 - Gilbert, David A1 - Heiner, Monika ED - Češka, Milan ED - Šafránek, David T1 - Derivation of a biomass proxy for dynamic analysis of whole genome metabolic models T2 - Computational Methods in Systems Biology, 16th International Conference, CMSB 2018, Brno, Czech Republic, September 12-14, 2018, Proceedings Y1 - 2018 SN - 978-3-319-99428-4 U6 - https://doi.org/10.1007/978-3-319-99429-1_3 N1 - referierter Beitrag SP - 39 EP - 58 PB - Springer CY - Cham ER - TY - GEN A1 - Gilbert, David A1 - Heiner, Monika A1 - Ghanbar, Leila A1 - Chodak, Jacek T1 - Spatial quorum sensing modelling using coloured hybrid Petri nets and simulative model checking T2 - BMC Bioinformatics Y1 - 2019 U6 - https://doi.org/10.1186/s12859-019-2690-z SN - 1471-2105 VL - 20 supplement 4 ER - TY - GEN A1 - Liu, Fei A1 - Sun, Wujie A1 - Heiner, Monika A1 - Gilbert, David T1 - Hybrid modelling of biological systems using fuzzy continuous Petri nets T2 - Briefings in Bioinformatics N2 - Integrated modelling of biological systems is challenged by composing components with sufficient kinetic data and components with insufficient kinetic data or components built only using experts’ experience and knowledge. Fuzzy continuous Petri nets (FCPNs) combine continuous Petri nets with fuzzy inference systems, and thus offer an hybrid uncertain/certain approach to integrated modelling of such biological systems with uncertainties. In this paper, we give a formal definition and a corresponding simulation algorithm of FCPNs, and briefly introduce the FCPN tool that we have developed for implementing FCPNs. We then present a methodology and workflow utilizing FCPNs to achieve hybrid (uncertain/certain) modelling of biological systems illustrated with a case study of the Mercaptopurine metabolic pathway. We hope this research will promote the wider application of FCPNs and address the uncertain/certain integrated modelling challenge in the systems biology area. KW - systems biology KW - integrated modelling KW - fuzzy continuous Petri nets KW - uncertainties KW - hybrid simulation Y1 - 2019 U6 - https://doi.org/10.1093/bib/bbz114 VL - 22(2021) SP - 438 EP - 450 ER - TY - RPRT A1 - Connolly, Shannon A1 - Gilbert, David A1 - Heiner, Monika T1 - From Epidemic to Pandemic Modelling N2 - We present a methodology for systematically extending epidemic models to multilevel and multiscale spatio-temporal pandemic ones. Our approach builds on the use of coloured stochastic and continuous Petri nets facilitating the sound component-based extension of basic SIR models to include population stratification and also spatio-geographic information and travel connections, represented as graphs, resulting in robust stratified pandemic metapopulation models. This method is inherently easy to use, producing scalable and reusable models with a high degree of clarity and accessibility which can be read either in a deterministic or stochastic paradigm. Our method is supported by a publicly available platform PetriNuts; it enables the visual construction and editing of models; deterministic, stochastic and hybrid simulation as well as structural and behavioural analysis. All the models are available as supplementary material, ensuring reproducibility. KW - SIR model KW - coloured Petri nets KW - stochastic Petri nets KW - continuous Petri nets KW - ODEs KW - simulation KW - geographic spatio-temporal 20 modelling KW - multiscale models Y1 - 2021 U6 - https://doi.org/10.48550/arXiv.2107.00835 PB - Cornell University CY - arXiv ER - TY - GEN A1 - Connolly, Shannon A1 - Gilbert, David A1 - Heiner, Monika T1 - From Epidemic to Pandemic Modelling T2 - Frontiers in Systems Biology N2 - We present a methodology for systematically extending epidemic models to multilevel and multiscale spatio-temporal pandemic ones. Our approach builds on the use of coloured stochastic and continuous Petri nets facilitating the sound component-based extension of basic SIR models to include population stratification and also spatio-geographic information and travel connections, represented as graphs, resulting in robust stratified pandemic metapopulation models. The epidemic components and the spatial and stratification data are combined together in these coloured models and built in to the underlying expanded models. As a consequence this method is inherently easy to use, producing scalable and reusable models with a high degree of clarity and accessibility which can be read either in a deterministic or stochastic paradigm. Our method is supported by a publicly available platform PetriNuts; it enables the visual construction and editing of models; deterministic, stochastic and hybrid simulation as well as structural and behavioural analysis. All models are available as Supplementary Material, ensuring reproducibility. All uncoloured Petri nets can be animated within a web browser at https://www-dssz.informatik.tu-cottbus.de/DSSZ/Research/ModellingEpidemics, assisting the comprehension of those models. We aim to enable modellers and planners to construct clear and robust models by themselves. KW - SIR model KW - coloured Petri nets KW - stochastic Petri nets KW - continuous Petri nets KW - ODEs KW - simulation KW - geographic spatio-temporal modelling KW - multiscale models Y1 - 2022 UR - https://www.frontiersin.org/articles/10.3389/fsysb.2022.861562/full U6 - https://doi.org/10.3389/fsysb.2022.861562 SN - 2674-0702 VL - 2 SP - 1 EP - 23 ER - TY - GEN A1 - Liu, Fei A1 - Heiner, Monika A1 - Gilbert, David T1 - Hybrid modelling of biological systems: current progress and future prospects T2 - Briefings in Bioinformatics N2 - Integrated modelling of biological systems is becoming a necessity for constructing models containing the major biochemical processes of such systems in order to obtain a holistic understanding of their dynamics and to elucidate emergent behaviours. Hybrid modelling methods are crucial to achieve integrated modelling of biological systems. This paper reviews currently popular hybrid modelling methods, developed for systems biology, mainly revealing why they are proposed, how they are formed from single modelling formalisms and how to simulate them. By doing this, we identify future research requirements regarding hybrid approaches for further promoting integrated modelling of biological systems. KW - biological modelling KW - hybrid modelling KW - modelling formalisms Y1 - 2022 UR - https://academic.oup.com/bib/article/23/3/bbac081/6555400 U6 - https://doi.org/10.1093/bib/bbac081 SN - 1477-4054 SN - 1467-5463 VL - 23 IS - 3 SP - 1 EP - 15 ER -