Hidde de Jong

• Mathematical modeling of biological systems
• Systems biology of microorganisms
• Analysis of metabolic networks and biotechnological applications
• Measurement of gene expression dynamics using fluorescent reporter genes and development of computer tools WellReader and WellInverter
• Identification of gene regulatory networks from experimental data
• Qualitative analysis of gene regulatory networks, using the computer tool Genetic Network Analyzer (GNA)

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Research projects

• MuSiHC: Multi-size Hybrid Cell Models (2025-2029), PEPR Biomasses, biotechnologies et technologies durables pour la chimie et les carburants (B-BEST)
• HyLife: Microbial risks associated with hydrogen underground storage in Europe (2023-2026), Clean Energy Transition (CET) Partnership
• ARBOREAL: Branching resource allocation processes for the analysis and inference of phenotypic growth variability (2023-2028), ANR Jeune Chercheuse (Aline Marguet)
• GERM: Growth-ratE Control in Mycobacteria (2021-2025), Inria associate-team with Francis Crick Institute, London
• Ctrl-AB: Optimization and control of the productivity of a bacterial-algal consortium (2021-2025), ANR
• Maximic: Optimal control of microbial cells by natural and synthetic strategies (2017-2021), ANR
• CoSoft: Control software for a system of mini-bioreactors (2017-2018), Inria ADT
• COSY: Real-time control of synthetic microbial communities (2017-2021), Inria Project Lab
• FluoBacTracker: Adaptation et valorisation scientifique du logiciel FluoBacTracker (2016-2017), InriaHub
• WellInverter: A web application for the analysis of time-series fluorescent reporter gene data (2016-2017), Development of innovative bioinformatics services for life sciences, Institut Français de Bioinformatique (IFB)
• RESET: Arrest and restart of the gene expression machinery in bacteria: from mathematical models to biotechnological applications (2012-2017), Investissements d’Avenir, Bioinformatique
• GemCO: Model reduction, experimental validation, and control for the gene expression machinery in E. coli (2010-2013), ANR Blanc
• ColAge: Natural and engineering solutions to the control of bacterial growth and aging (2009-2013), Large-Scale Initiative Action INRIA-INSERM
• MetaGenoReg: Towards an understanding of the interrelations between metabolic and gene regulation: E. coli carbon metabolism as a test case (2006-2010), ANR Biologie systémique (BIOSYS)
• EC-MOAN: Scalable modeling and analysis techniques to study emergent cell behavior: Understanding the E. coli stress response (2007-2009), NEST-2005-2 PATHFINDER
• COBIOS: Engineering and control of biological systems: A new way to tackle complex diseases and biotechnological innovation (2007-2009), NEST-2005-2 PATHFINDER
• Experimental verification of the predictions of a model of the E. coli nutritional stres response (2005-2007), CPER
• Hygeia: Hybrid systems for biochemical network modeling and analysis (2005-2007), NEST-2003-1 ADVENTURE
• BacAttract: Theoretical and experimental analysis of the attractors of genetic regulatory networks: Global regulation of transcription in Escherichia coli and Synechocystis PCC 6803 (2003-2006), ACI IMPBio
• GDyn: Dynamic analysis of genetic regulatory networks (2002-2004), Action de Recherche Coopérative INRIA
• Validation of models of genetic regulatory networks: Global regulation of transcription in Escherichia coli and Synechocystis PCC 6803 (2002-2004), Programme Bioinformatique inter-EPST
• Modeling and simulation of genetic regulatory networks: Signal transduction by cyclic nucleotides in the cyanobacterium Synechocystis PCC 6803 (2000-2002), Programme Bioinformatique inter-EPST

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Courses

I give courses in bioinformatics and systems biology, in particular on the modeling and simulation of bacterial regulatory networks, at the Institut National des Sciences Appliquées (INSA) in Lyon and in the Advanced Lecture Course on Computational Systems Biology (CompSysBio), which is held every two years in Aussois (France). The latest version of these courses, as well as a set of computer exercises for the integrated modeling of genetic and metabolic networks are available from the INSA course web site. I have also participated in the organization of the summer school Economic Principles in Cell Biology, held in Paris in 2023 and 2024, and in Vienna in 2025.

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Organizational activities

I have been a member of the editorial board of the Journal of Mathematical Biology (2008-), the ACM/IEEE Transactions on Computational Biology and Bioinformatics (2005-2019), and Biosystems (2010-2024). I also served on the Scientific Advisory Board of the Microbiology and Food Chain department of INRAE (2012-2024). Since July 2021, I have been the scientific director (délégué scientifique) of the INRIA Grenoble – Rhône-Alpes research centre.

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Selected publications

2025

• A. Belcour, L. Megy, S. Stephant, C. Michel, S. Rad, P. Bombach, N. Dopffel, H. de Jong, D. Ropers. Predicting coarse-grained representations of biogeochemical cycles from metabarcoding data. Bioinformatics, to appear. Special issue ISMB/ECCB 2025
• A. Pavlou , E. Cinquemani , C. Pinel , N. Giordano , M. van Melle-Gateau, I. Mihalcescu, J. Geiselmann, H. de Jong. Single-cell data reveal heterogeneity of investment in ribosomes across a bacterial population. Nature Communications, 16:285, 2025. Editors’ Highlight in Nature Communications, in the category Microbiology and infectious diseases

2024

• T. Clavier, C. Pinel, H. de Jong, J. Geiselmann. Improving the genetic stability of bacterial growth control for long-term bioproduction. Biotechnology and Bioengineering,121(9):2808-2819, 2024

2023

• V. Baldazzi, D. Ropers, J.-L. Gouzé, T. Gedeon, H. de Jong. Resource allocation accounts for the large variability of rate-yield phenotypes across bacterial strains. eLife, 12:e79815, 2023
• H. de Jong, D. Giannari, D. Oyarzún, S. Waldherr, A. Yabo. Optimal cell behavior in time. In: Economic Principles in Cell Biology, 2023. Free, community-wide, on-line textbook
• O. Golan, H.J. Hindley, H. de Jong, M. Köbis, E. Pascual Garcia, A.Y. Weiße. Models of growing cells. In: Economic Principles in Cell Biology, 2023. Free, community-wide, on-line textbook
• C. Martínez, E. Cinquemani, H. de Jong, J.-L. Gouzé. Optimal protein production by a synthetic microbial consortium: Coexistence, distribution of labor, and syntrophy. Journal of Mathematical Biology, 87(1):23, 2023

2022

• A. Yabo, J.B. Caillau, J.L. Gouzé, H. de Jong, F. Mairet. Dynamical analysis and optimization of a generalized resource allocation model of microbial growth. SIAM Journal on Applied Dynamical Systems, 21(1):137-165, 2022
• A. Pavlou, E. Cinquemani, J. Geiselmann, H. de Jong. Maturation models of fluorescent proteins are necessary for unbiased estimates of promoter activity. Biophysical Journal, 121(21):4179-4188

2021

• D. Ropers, Y. Couté, L. Faure, S. Ferré, D. Labourdette, A. Shabani, L. Trouilh, P. Vasseur, G. Corre, M. Ferro, M.-A. Teste, J. Geiselmann, H. de Jong. A multi-omics study of bacterial growth arrest in a synthetic biology application. ACS Synthetic Biology, 10(11):2910-2926
• M. Chaves, H. de Jong. Qualitative modeling, analysis and control of synthetic regulatory circuits. In: F. Menolascine (ed.), Synthetic Gene Circuits: Methods and Protocols, Methods in Molecular Biology 2229, Humana Press, New York, 2021, 1-40
• F. Mairet, J.-L. Gouzé, H. de Jong. Optimal proteome allocation and the temperature dependence of microbial growth laws. npj Systems Biology and Applications, 7:14, 2021

2020

• M. Mauri, J.-L. Gouzé, H. de Jong, E. Cinquemani. Enhanced production of heterologous proteins by a synthetic microbial community: Conditions and trade-offs. PLoS Computational Biology, 16(4):e1007795, 2020

2019

• E. Cinquemani, F. Mairet, I. Yegorov, H. de Jong, J.-L. Gouzé. Optimal control of bacterial growth for metabolite production: The role of timing and costs of control. Proceedings of the 17th European Control Conference (ECC 2019), Naples, Italy, 2019
• Y. Martin, M. Page, C. Blanchet, H. de Jong. WellInverter: A web application for the analysis of fluorescent reporter gene data. BMC Bioinformatics, 20(1):309, 2019
• S. Pinhal, D. Ropers, J. Geiselmann, H. de Jong. Acetate metabolism and the inhibition of bacterial growth by acetate. Journal of Bacteriology, 201(13):e00147-19, 2019
• I. Yegorov, F. Mairet, H. de Jong, J.-L. Gouzé. Optimal control of bacterial growth for the maximization of metabolite production. Journal of Mathematical Biology, 78(4):985–1032, 2019

2018

• A. Kremling, J. Geiselmann, D. Ropers, H. de Jong. An ensemble of mathematical models showing diauxic growth behavior.  BMC Systems Biology, 21(1):82, 2018

2017

• E. Cinquemani, V. Laroute, M. Cocaign-Bousquet, H. de Jong, D. Ropers. Estimation of time-varying growth, uptake and excretion rates from dynamic metabolomics data. Bioinformatics, 33 (14), i301-i310, 2017. Special issue ISMB/ECCB 2017
• H. de Jong, S. Casagranda, N. Giordano, E. Cinquemani, D. Ropers, J. Geiselmann, J.-L. Gouzé. Mathematical modeling of microbes: Metabolism, gene expression, and growth. Journal of the Royal Society Interface, 14(136):20170502, 2017
• H. de Jong, , J. Geiselmann, D. Ropers. Resource reallocation in bacteria by reengineering the gene expression machinery. Trends in Microbiology, 25(6):480-493, 2017

2016

• N. Giordano, F. Mairet, J.-L. Gouzé, J. Geiselmann, H. de Jong. Dynamical allocation of cellular resources as an optimal control problem: Novel insights into microbial growth strategies. PLoS Computational Biology, 12(3): e1004802, 2016

2015

• J. Izard, C. Gomez Balderas, D. Ropers, S. Lacour, X. Song, Y. Yang, A.B. Lindner, J. Geiselmann, H. de Jong. A synthetic growth switch based on controlled expression of RNA polymerase. Molecular Systems Biology, 11(11):840, 2015
• H. de Jong, J. Geiselmann. Fluorescent reporter genes and the analysis of bacterial regulatory networks. In: Proceedings of the Second International Workshop (HSB 2013) and Third International Workshop on Hybrid Systems Biology (HSB 2013 and HSB 2014), In: O. Maler, A. Halasz, T. Dang, C. Piazza (eds), LNBI 7699, Springer-Verlag, Berlin, 2015, 1-24
• A. Kremling, J. Geiselmann, D. Ropers, H. de Jong. Understanding carbon catabolite repression in Escherichia coli using quantitative models. Trends in Microbiology. 23(2):99-109, 2015
• D. Stefan, C. Pinel, S. Pinhal, E. Cinquemani, J. Geiselmann, H. de Jong. Inference of quantitative models of bacterial promoters from time-series reporter gene data. PLoS Computational Biology, 11(1):e1004028, 2015
• V. Zulkower, M. Page, D. Ropers, J. Geiselmann, H. de Jong. Robust reconstruction of gene expression profiles from reporter gene data using linear inversion. Bioinformatics, 31(12):i71-i79, 2015. Special issue ISMB/ECCB 2015

2014

• V. Acary, H. de Jong, B. Brogliato. Numerical simulation of piecewise-linear models of gene regulatory networks using complementarity systems. Physica D: Nonlinear Phenomena, 269:103-119, 2014
• M. Trauchessec, M. Jaquinod, A. Bonvalot, V. Brun, C. Bruley, D. Ropers, H. de Jong, J. Garin, G. Bestel-Corre, M. Ferro. Mass spectrometry-based workflow for accurate quantification of E. coli enzymes: how proteomics can play a key role in metabolic engineering. Molecular and Cellular Proteomics, 13(4):954-968, 2014

2013

• G. Baptist, C. Pinel, C. Ranquet, J. Izard, D. Ropers, H. de Jong, J. Geiselmann. A genome-wide screen for identifying all regulators of a target gene. Nucleic Acids Research, 41(17):e164, 2013
• S. Berthoumieux, M. Brilli, D. Kahn, H. de Jong, E. Cinquemani. On the identifiability of metabolic network models. Journal of Mathematical Biology, 67(6-7):1795-1832, 2013
• S. Berthoumieux, H. de Jong, G. Baptist, C. Pinel, C. Ranquet, D. Ropers, J. Geiselmann. Shared control of gene expression in bacteria by transcription factors and global physiology of the cell. Molecular Systems Biology, 9:634, 2013. Editors’ choice in Science
• C. Chaouiya, D. Berenguier, S.M. Keating, A. Naldi, M.P. van Iersel, N. Rodriguez, A. Dräger, F. Büchel, T. Cokelaer, B. Kowal, B. Wicks, E. Gonçalves, J. Dorier, M. Page, P.T. Monteiro, A. von Kamp, I. Xenarios, H. de Jong, M. Hucka, S. Klamt, D. Thieffry, N. Le Novère, J. Saez-Rodriguez, T. Helikar. SBML Qualitative Models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools. BMC Systems Biology, 7(1):135, 2013

2012

• V. Baldazzi, N. Bertin, H. de Jong, M. Génard. Towards multi-scale plant models: integrating cellular networks. Trends in Plant Science, 17(12):728-736, 2012
• V. Baldazzi, D. Ropers, J. Geiselmann, D. Kahn, H. de Jong. Importance of metabolic coupling for the dynamics of gene expression following a diauxic shift in E. coli. Journal of Theoretical Biology, 295:100-115, 2012
• G. Batt, B. Besson, P.-E. Ciron, H. de Jong, E. Dumas, J. Geiselmann, R. Monte, P.T. Monteiro, M. Page, F. Rechenmann, D. Ropers. Genetic Network Analyzer: A tool for the qualitative modeling and simulation of bacterial regulatory networks. In: J. van Helden, A. Toussaint, D. Thieffry (eds), Bacterial Molecular Networks: Methods and Protocols, Methods in Molecular Biology, Humana Press, Springer, New York, 2012, 439-462

2011

• S. Berthoumieux, M. Brilli, H. de Jong, D. Kahn, E. Cinquemani. Identification of metabolic network models from incomplete high-throughput datasets. Bioinformatics, 17(13):i186-i195, 2011. Special issue ISMB/ECCB 2011. Outstanding student paper award at ISMB/ECCB 2011
• R. Mateescu, P. Monteiro, E. Dumas, H. de Jong. CTRL: Extension of CTL with regular expressions and fairness operators to verify genetic regulatory networks. Theoretical Computer Science, 412(26):2854-2883, 2011. Special issue CMSB 2008
• D. Ropers, V. Baldazzi, H. de Jong. Model reduction using piecewise-linear approximations preserves dynamic properties of the carbon starvation response in Escherichia coli. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 8(1):166-181, 2011
• R. Silva-Rocha, H. de Jong, J. Tamames, V. de Lorenzo. The logic layout of the TOL network of Pseudomonas putida pWW0 plasmid stems from a metabolic amplifier motif (MAM) that optimizes biodegradation of m-xylene. BMC Systems Biology, 5:191, 2011

2010

• V. Baldazzi, D. Ropers, Y. Markowicz, D. Kahn, J. Geiselmann, H. de Jong. The carbon assimilation network in Escherichia coli is densely connected and largely sign-determined by directions of metabolic fluxes. PLoS Computational Biology, 6(6):e1000812, 2010
• G. Batt, M. Page, I. Cantone, G. Goessler, P. Monteiro, H. de Jong. Efficient parameter search for qualitative models of regulatory networks using symbolic model checking. Bioinformatics, 26(18):i603-i610, 2010. Special issue ECCB 2010
• F. Boyer, B. Besson, G. Baptist, J. Izard, C. Pinel, D. Ropers, J. Geiselmann, H. de Jong. WellReader: A MATLAB program for the analysis of fluorescence and luminescence reporter gene data. Bioinformatics, 26(9):1262-1263, 2010
• H. de Jong, C. Ranquet, D. Ropers, C. Pinel, J. Geiselmann. Experimental and computational validation of models of fluorescent and luminescent reporter genes in bacteria. BMC Systems Biology, 4:55, 2010

2009

• H. de Jong. Vers la cellule virtuelle. DocSciences, 8:20-25, 2009
• P.T. Monteiro, E. Dumas, B. Besson, R. Mateescu, M. Page, A.T. Freitas, H. de Jong. A service-oriented architecture for integrating the modeling and formal verification of genetic regulatory networks. BMC Bioinformatics, 10:450, 2009
• D. Ropers, H. de Jong, J. Geiselmann. Mathematical modeling of genetic regulatory networks: Stress responses in Escherichia coli. In: P. Fu, M. Latterich, S. Panke (eds), Systems and Synthetic Biology, Wiley & Sons, Hoboken NJ, 2009, 235-271

2008

• G. Batt, H. de Jong, M. Page, J. Geiselmann. Symbolic reachability analysis of genetic regulatory networks using qualitative abstractions. Automatica, 44(4):982-989, 2008. For longer version, see Technical Report INRIA, RR-6136
• H. de Jong. Qualitative modeling and simulation of bacterial regulatory networks. In: A. Uhrmacher, M. Heiner (eds.), Proceedings of the 6th International Conference on Computational Methods in Systems Biology (CMSB-08), LNCS 5307, Springer-Verlag, Berlin, 2008, 1
• H. de Jong, M. Page. Search for steady states of piecewise-linear differential equation models of genetic regulatory networks. ACM/IEEE Transactions on Computational Biology and Bioinformatics, 5(2):508-522, 2008
• S. Drulhe, G. Ferrari-Trecate, H. de Jong. The switching threshold reconstruction problem for piecewise affine models of genetic regulatory networks. IEEE Transactions on Automatic Control & IEEE Transactions on Circuits and Systems I, 53(1):153-165, 2008. Joint special issue on systems biology
• R. Mateescu, P.T. Monteiro, E. Dumas, H. de Jong. Computation Tree Regular Logic for genetic regulatory networks. In: S. Cha, J.-Y. Choi, M. Kim, I. Lee, M. Viswanathan (eds.), Proceedings of the 6th International Symposium on Automated Technology for Verification and Analysis (ATVA’08), Lecture Notes in Computer Science 5311, Springer, Berlin, 2008, 48-63. For longer version, see Technical Report INRIA, RR-6521
• P.T. Monteiro, D. Ropers, R. Mateescu, A.T. Freitas, H. de Jong. Temporal logic patterns for querying dynamic models of cellular interaction networks. Bioinformatics, 24(16) :i227-i233, 2008. Special issue ECCB-2008
• P.T. Monteiro, D. Ropers, R. Mateescu, A.T. Freitas, H. de Jong. Temporal logic patterns for querying qualitative models of genetic regulatory networks. In: M. Ghallab, C.D. Spyropoulos, N. Fakotakis, N. Avouris (eds.), Proceedings of 18th European Conference on Artificial Intelligence (ECAI 2008), IOS Press, Amsterdam, 2008, 229-233
• R. Porreca, S. Drulhe, H. de Jong, G. Ferrari-Trecate. Structural identification of piecewise-linear models of genetic regulatory networks. Journal of Computational Biology, 15(10):1365-1380, 2008

2007

• G. Batt, H. de Jong, J. Geiselmann, J.-L. Gouzé, M. Page, D. Ropers, T. Sari, D. Schneider. Analyse qualitative de la dynamique de réseaux de régulation génique par des modèles linéaires par morceaux. Technique et Science Informatique, 26(1-2):11-45, 2007
• F. Grognard, H. de Jong, J.-L. Gouzé. Piecewise-linear models of genetic regulatory networks: Theory and example. In: I. Queinnec, S. Tarbouriech, G. Garcia, S. Niculescu (eds), Biology and Control Theory: Current Challenges, Lecture Notes in Control and Information Sciences (LNCIS) 357, Springer-Verlag, Berlin, 2007, 137-159
• M.W.J.M. Musters, H. de Jong, P.P.J. van den Bosch, N.A.W. van Riel. Qualitative analysis of nonlinear biochemical networks with piecewise-affine functions. In: A. Bemporad, A. Bicchi, G. Buttazzo (eds), Hybrid Systems: Computation and Control (HSCC 2007), Lecture Notes in Computer Science 4416, Springer-Verlag, Berlin, 2007, 727-730
• D. Ropers, H. de Jong, J. Geiselmann. Modélisation de la réponse au stress nutritionnel de la bactérie Escherichia coli, Biofutur, 275:36-39, 2007

2006

• G. Batt, R. Casey, H. de Jong, J. Geiselmann, J.-L. Gouzé, M. Page, D. Ropers, T. Sari, D. Schneider. Qualitative analysis of the dynamics of genetic regulatory networks using piecewise-linear models. In: E. Pecou, S. Martinez, A. Maass (eds.), Mathematical and Computational Methods in Biology, Editions Hermann, Paris, 2006, 206-239
• R. Casey, H. de Jong, J.-L. Gouzé. Piecewise-linear models of genetic regulatory networks: Equilibria and their stability. Journal of Mathematical Biology, 52(1):27-56, 2006
• C. Chaouiya, H. de Jong, D. Thieffry. Dynamical modeling of biological regulatory networks. BioSystems, 84(2):77-80, 2006. Introduction to special issue
• H. de Jong, D. Ropers. Strategies for dealing with incomplete information in the modeling of molecular interaction networks. Briefings in Bioinformatics, 7(4):354-363, 2006
• S. Drulhe, G. Ferrari-Trecate, H. de Jong, A. Viari. Reconstruction of switching thresholds in piecewise-affine models of genetic regulatory networks. In: J. Hespanha, A. Tiwari (eds), Hybrid Systems: Computation and Control, HSCC 2006, Lecture Notes in Computer Science 3927, Springer-Verlag, Berlin, 2006, 184-199
• H. de Jong, D. Ropers. Qualitative approaches towards the analysis of genetic regulatory networks. In: Z. Szallasi, V. Periwal, J. Stelling (eds), System Modeling in Cellular Biology: From Concepts to Nuts and Bolts, MIT Press, Cambridge, MA, 2006, 125-148
• D. Ropers, H. de Jong, M. Page, D. Schneider, J. Geiselmann. Qualitative simulation of the carbon starvation response in Escherichia coli. BioSystems, 84(2):124-152, 2006
• I. Vatcheva, O. Bernard, H. de Jong, N.J.I. Mars. Experiment selection for the discrimination of semi-quantitative models of dynamical systems. Artificial Intelligence, 170(4-5):472-506, 2006

2005

• G. Batt, D. Ropers, H. de Jong, J. Geiselmann, R. Mateescu, M. Page, D. Schneider. Analysis and verification of qualitative models of genetic regulatory networks : A model-checking approach. In: L.P. Kaelbling (ed.), Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI-05), Morgan Kauffman, San Francisco, CA, 2005, 370-375
• G. Batt, D. Ropers, H. de Jong, J. Geiselmann, R. Mateescu, M. Page, D. Schneider. Validation of qualitative models of genetic regulatory networks by model checking: Analysis of the nutritional stress response in Escherichia coli. Bioinformatics, 21(Suppl 1) :i19-i28, 2005. Special issue ISMB-2005
• G. Batt, H. de Jong, J. Geiselmann, M. Page, D. Ropers, D. Schneider. Qualitative analysis and verification of hybrid models of genetic regulatory networks: Nutritional stress response in Escherichia coli. M. Morari, L. Thiele (eds), Hybrid Systems: Computation and Control (HSCC 2005), Lecture Notes in Computer Science 3414, Springer-Verlag, Berlin, 2005, 134-150
• H. de Jong. Qualitative simulation and related approaches for the analysis of dynamical systems. Knowledge Engineering Review, 19(2):93-132, 2005
• H. de Jong, J. Geiselmann. Modeling and simulation of genetic regulatory networks by ordinary differential equations. In: J. Chen, E.R. Dougherty, I. Shmulevich, Z.J. Wang (eds), Genomic Signal Processing and Statistics, Hindawi Publishing Corporation, New York, 2005, 201‑239
• H. de Jong, D. Ropers, C. Chaouiya, D. Thieffry. Modélisation, analyse et simulation de réseaux de régulation génique. Biofutur, 252:36-40, 2005
• C. Ranquet, A. Toussaint, H. de Jong, G. Maenhaut-Michel, J. Geiselmann. Control of bacteriophage Mu lysogenic repression. Journal of Molecular Biology, 353(1):186-195, 2005
• F. Rechenmann, H. de Jong. Le vivant en équations. La Recherche, 383:32-37, 2005

2004

• G. Batt, D. Bergamini, H. de Jong, H. Gavarel, R. Mateescu. Model checking genetic regulatory networks using GNA and CADP. In: Eleventh International SPIN Workshop on Model Checking of Software (SPIN 2004), Lecture Notes in Computer Science 2989, Springer-Verlag, Berlin, 2004, 158-163
• H. de Jong. Modélisation et simulation qualitative de réseaux de régulation génique. Report presented for obtaining the `Habilitation à diriger des recherches’, Joseph Fourier University, Grenoble, 2004
• H. de Jong, J. Geiselmann. Modélisation et simulation de réseaux de régulation génique par des équations différentielles ordinaires. In: J.-F. Boulicaut, O. Gandrillon (eds), Informatique pour l’analyse du transcriptome, Hermès, Paris, 2004, 143-185
• H. de Jong, J. Geiselmann, G. Batt, C. Hernandez, M. Page. Qualitative simulation of the initiation of sporulation in Bacillus subtilis. Bulletin of Mathematical Biology, 66(2):261-300, 2004
• H. de Jong, J.-L. Gouzé, C. Hernandez, M. Page, T. Sari, J. Geiselmann. Qualitative simulation of genetic regulatory networks using piecewise-linear models. Bulletin of Mathematical Biology, 66(2):301-340, 2004. Recommended by Faculty of 1000
• D. Eveillard, D. Ropers, H. de Jong, C. Branlant, A. Bockmayr. A multi-scale constraint programming model of alternative splicing regulation. Theoretical Computer Science, 135(1):3-24, 2004

2003

• H. de Jong. Simulation qualitative. In: L. Travé-Massuyès and P. Dague (eds), Modèles et raisonnements qualitatifs, Hermès, Paris, 2003, 269-329
• H. de Jong. Modeling and simulation of genetic regulatory networks. In: L. Benvenuti, A. De Santis, L. Farina (eds), Positive Systems (POSTA 2003), Lectures Notes in Control and Information Sciences 294, Springer-Verlag, Berlin, 2003, 111-118
• H. de Jong, J. Geiselmann, C. Hernandez, M. Page. Genetic Network Analyzer: Qualitative simulation of genetic regulatory networks. Bioinformatics, 19(3):336-344, 2003. Recommended by Faculty of 1000
• H. de Jong, J. Geiselmann, D. Thieffry. Qualitative modeling and simulation of developmental regulatory networks. In: S. Kumar, P.J. Bentley (eds), On Growth, Form, and Computers, Academic Press, London, 2003, 109-134
• H. de Jong, J.-L. Gouzé, C. Hernandez, M. Page, T. Sari, J. Geiselmann. Hybrid modeling and simulation of genetic regulatory networks: A qualitative approach. In: A. Pnueli, O. Maler (eds), Hybrid Systems: Computation and Control (HSCC 2003), Lecture Notes in Computer Science 2623, Springer-Verlag, Berlin, 2003, 267-282
• D. Eveillard, D. Ropers, H. de Jong, C. Branlant, A. Bockmayr. Multiscale modeling of alternative splicing regulation. In: C.Priami (ed.), Computational Methods in Systems Biology (CMSB-03), Lecture Notes in Computer Science 2602, Springer-Verlag, Berlin, 2003, 75-87
• D. Schneider, A. Latifi, H. de Jong, J. Geiselmann. Dynamics and simulation of the genetic regulatory networks in bacteria. Recent Research Developments in Genetics, 3:55-83, 2003

2002

• H. de Jong. Modeling and simulation of genetic regulatory systems: A literature review. Journal of Computational Biology, 9(1):67-103, 2002. Top 5 most cited papers
• H. de Jong, J.-L. Gouzé, C. Hernandez, M. Page, T. Sari, J. Geiselmann. Dealing with discontinuities in the qualitative simulation of genetic regulatory networks. In: F. van Harmelen (ed.), Proceedings of Fifteenth European Conference on Artifical Intelligence (ECAI-02), IOS Press, Amsterdam, 2002, 412-416
• C. Hernandez, H. de Jong, J. Geiselmann, M. Page. VisualGNA : A graphical interface for the qualitative simulation of genetic regulatory networks. In: J. Nicolas, C. Thermes (eds), Recueil des Actes des Journées Ouvertes Biologie Informatique Mathématiques (JOBIM 2002), Saint-Malo, 2002, 335-336
• D. Thieffry, H. de Jong. Modélisation, analyse et simulation des réseaux génétiques. Médécine/Sciences, 18(4):492-502, 2002

2001

• H. de Jong, M. Page, C. Hernandez, J. Geiselmann. Qualitative simulation of genetic regulatory networks: Method and application, In: B. Nebel (ed.), Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI-01), Morgan Kaufmann, San Francisco, CA, 2001, 67-73
• I. Vatcheva, O. Bernard,H.de Jong, J.-L. Gouzé, N.J.I. Mars. Discrimination of semi-quantitative models by experiment selection: Method and application in population biology. In: B. Nebel (ed.), Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI-01), Morgan Kaufmann, San Francisco, CA, 2001, 74-79

2000

• H.de Jong, M. Page. Qualitative simulation of large and complex genetic regulatory systems. In: W. Horn (ed.), Proceedings of the Fourteenth European Conference on Artificial Intelligence (ECAI 2000), IOS Press, Amsterdam, 2000, 141-145
• I. Vatcheva, H. de Jong, N.J.I. Mars. Selection of perturbation experiments for model discrimination. In: W. Horn (ed.), Proceedings of the Fourteenth European Conference on Artificial Intelligence (ECAI 2000), IOS Press, Amsterdam, 2000, 191-195

1999

• H. de Jong, F. van Raalte. Comparative envisionment construction: A technique for the comparative analysis of dynamical systems. Artificial Intelligence, 115(2):145-214, 1999
• H. de Jong, N.J.I. Mars, P.E. van der Vet. Computer-supported resolution of measurement conflicts: A case-study in materials science. Foundations of Science, 4(4):427-461, 1999
• I. Vatcheva, H. de Jong. Semi-quantitative comparative analysis. In: T.D. Dean (ed.), Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99), Morgan Kaufmann, San Francisco, CA, 1999, 1034-1040

1998

H. de Jong. Computer-supported analysis of scientific measurements. CTIT Ph.D. Series 98-23, Ph.D. thesis in Computer Science, University of Twente, Enschede, the Netherlands, 1998

1997

• H. de Jong, A. Rip. The computer revolution in science: Steps towards the realization of computer-supported discovery environments. Artificial Intelligence, 91(2):225-256, 1997
• H. de Jong, F. van Raalte. Comparative analysis of structurally different dynamical systems. In: M.E. Pollack(ed.), Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI-97), Morgan Kaufmann, San Francisco, CA, 486-491, 1997

1996

• H. de Jong, N.J.I. Mars, P.E. van der Vet. CEC: Comparative analysis by envisionment construction. In: W. Wahlster (ed.), Proceedings of the Twelfth European Conference on Artificial Intelligence (ECAI-96), John Wiley & Sons, Chichester, 1996, 476-480

1995

• H. de Jong, A. Rip. Ontdekkingspraktijk in plaats van logica: Wetenschappelijk ontdekken in computerondersteunde ontdekkingsomgevingen. Kennis en Methode, XIX(2):131-159, 1995

1994

• N.J.I. Mars, H. de Jong, P.-H. Speel, W.G. ter Stal, P.E. van der Vet. Semi-automatic knowledge acquisition in Plinius: An engineering approach. In: B. Gaines, M. Musen (eds), Proceedings of the Eighth Banff Knowledge Acquisition for Knowledge-based Systems Workshop (KAW-94), Banff, 1994, 4-1-4-15

1993

• H. de Jong, N.J.I. Mars, P.E. van der Vet. Consistency of scientific knowledge bases. In: A.D. Preece, K. Bellman, J. Combs, C. Culbert, D. O’Leary, L. Miller, N. Sizemore, R. Stachowitz (eds), Working Notes of the AAAI-93 Workshop on Validation and Verification of Knowledge-Based Systems, AAAI Press, Menlo Park, CA, 1993, 64-65

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