Principal Investigators :

Andrea PARMEGGIANI (Professor, University of Montpellier)

Ovidiu RADULESCU (Professor, University of Montpellier)


BUFFARD Marion Doctorante marion.buffard arobase umontpellier.fr



luca.ciandrini arobase univ-montp2.fr

HODGKINSON Arran Doctorant arran.hodgkinson arobase umontpellier.fr


Professor UM2

andrea.parmeggiani arobase univ-montp2.fr


Professor UM2

ovidiu.radulescu arobase univ-montp2.fr

Our team develops physical, mathematical and computer science approaches for the understanding of the functioning of biological systems. At the centre of our approaches is the multi-scale modelling of the biological processes by using statistical physics, dynamical systems and stochastic processes techniques. Our priority is to identify system’s critical targets and essential mechanisms. This knowledge can be used to elaborate new therapies against complex diseases.


Main aims of research :

Aim 1 : Large regulatory networks: from molecular interactions to biological function

We develop mathematical methods for reconstruction and analysis of large biochemical networks involved in cellular signalling and metabolism. These networks are described as complex systems of interacting molecules, together with their dynamics in space and in time. Although our approaches can be applied to the understanding of regulatory processes in all organisms, we study with particular emphasis networks of higher eukaryotes, involved in systems biology of human health and disease. To improve the effectiveness of mathematical modelling we take into account and benefit from notable properties of biological regulation networks such as modularity, multiscaleness, and robustness. Some recent developments and projects: i) cross-talk of signaling pathways in cancer (Ewing sarcoma, cervical cancer); ii) cell cycle hybrid modeling; iii) lipid metabolism in various species (fatty acid balance in mice liver during fasting, phospholipid synthesis in Plasmodium falciparum); iv) canalization of early development stages in dipteran insects; v) robustness of complex regulatory networks by dimension compression; vi) stochastic networks.

Aim 2 : Biological physics of molecular assemby: from individual molecule to supramolecular organization and dynamics

Using statistical mechanics principles, we develop physical models of cellular processes at supramolecular scale, such as protein transport over complex filament networks or protein-protein interactions on nanotubular structures. For exemple, we want to understand whether and how an elastic substrate can determine protein mutual interactions, even at long range, how these interactions can influence nucleation, pattern formation, transport, organization of protein assemblies as well as protein sorting. More generally, we are interested in non-equilibrium collective phenomena of nucleation, growth and transport through the cytoplasm, over membranes, filaments or complex filament networks. This knowledge is relevant also to model experiments in silico and interact with experimentalists in biology and biophysics.

Some recent developments and projects :
i) Mechanical instabilities of tubular lipid membranes, protein/protein and protein/membrane interactions,
ii) collective dynamical properties of low-dimensional lattices gas mimicking motor protein intracellular processes;
iii) tubuline and microtubule response under a hydrostatic pressure;
iv) nucleation growth and maturation of Mycobacterium smegmatis biofilms,
v) in silico description of fluorescent microscopy and spectroscopy experiments.

Past projects :
i) non-equilibrium and stochastic properties of a single molecular motor;
ii) mechanisms of force production and transport of acto-myosin systems under ATP depletion.

Aim 3: Multiscale approaches: from individual molecule and molecular interactions to virtual cell

This goal combines 1) and 2). By using across scales descriptions, we aim to integrate in our models both physical processes and regulatory networks. Our methodology can be described as hierarchical modelling. It allows descriptions of biological systems at different scales and it is based on model reduction and model conversion techniques. By setting solid theoretical basis for hierarchical modelling, we contribute to the larger international effort endeavoring the future creation of an integrated model of the whole cell (virtual cell).


- 2015 Publications -

Sanchez A., Cattoni D., Walter J.-C., Rech J., Parmeggiani A., Nollmann M., Bouet J.-Y. (2015) Stochastic Self-Assembly of ParB Proteins Builds the Bacterial DNA Segregation Apparatus, Cell Systems, vol. 1 p.163-173

Golushko I.Y., Rochal S.B., Parmeggiani A., Lorman V.L. (2015) Instabilities and shape variation phase transitions in tubular lipid membranes, arXiv preprint arXiv :1501.00258

Baiesi M., Carlon E., Parmeggiani A. (2015) Fundamental Problems in Statistical Physics XIII Special Issue, Physica A Statistical Mechanics and its Applications 418, 1-5

Ciandrini L. (2015) Molecular motors with a stepping cycle: from theory to experiments.  Proceedings of Traffic and Granular Flow '13, pp 619-627, Springer

Samal S.S., Grigoriev D., Fröhlich H., Radulescu O. (2015): Analysis of reaction network systems using tropical geometry. In: V.P. Gerdt, W. Koepf, W.M. Seiler, E.V. Vorozhtsov (eds.) Computer Algebra in Scientific Computing, 17th International Workshop (CASC 2015), Lecture Notes in Computer Science, vol. 9301, pp. 422--437. Springer, Aachen, Germany

Radulescu O., Vakulenko S., Grigoriev D. (2015) : Model reduction of biochemical reactions networks by tropical analysis methods. Mathematical Models of Natural Phenomena 10(3), 124-138

Fardin M-A., Radulescu O., Morozov A., Cardoso O., and Lerouge S..  (2015) Stress diffusion in shear banding wormlike micelles. Journal of Rheology, in press

Radulescu O., Samal S.S., Naldi A., Grigoriev D. and Weber A. (2015) Symbolic dynamics of biochemical pathways as finite state machines. 13th International Conference (CMSB 2015), Lecture Notes in Computer Science, in press.


- 2014 Publications -

Ciandrini L., Neri I., Walter J.C., Dauloudet O., Parmeggiani A., Motor protein traffic regulation by supply-demand balance of resources. Physical Biology 11 (2014), 056006-1/17, selected as the Physical Biology Highlights of 2014, http ://iopscience.iop.org/1478-3975/page/Highlights-of-2014

Rohani N., Parmeggiani A., Winklbauer R., Fagotto F. Variable Combinations of Specific Ephrin Ligand/Eph Receptor Pairs Control Embryonic Tissue Separation PLoS Biology 12 (2014), e1001955-1/21, Synopsis by R. Robinson,“Bind and Separate : How Ephrins and Their Receptors Create Tissue Boundaries”, PLoS, Biol 12 (2014), e1001956.

Ciandrini L., Romano M.C., Parmeggiani A., Stepping and crowding of molecular motors : statistical kinetics from an exclusion process perspective - Biophysical Journal 107 (2014), 1176-1184

Parmeggiani A., Neri I., Kern N. (2014) Modelling Collective Cytoskeletal Transport and Intracellular Traffic - The Impact of Applications on Mathematics - 1-25

Noel V., Grigoriev D., Vakulenko S., Radulescu O. (2014) Tropical and Idempotent Mathematics and Applications, Contemporary Mathematics vol. 616, chap. Tropicalization and tropical equilibration of chemical reactions. American Mathematical Society.

Soliman S., Fages F., Radulescu O. (2014) : A constraint solving approach to model reduction by tropical equilibration. Algorithms for Molecular Biology 9(1), 24.


- 2013 Publications -

Raguin A.,  Parmeggiani A., Kern N. (2013) Role of network junctions for the totally asymmetric simple exclusion process Physical Review E 88 - 042104-1/15

Neri I., Kern N., Parmeggiani A. (2013) Exclusion processes on networks as models for cytoskeletal transport New Journal of Physics 15 -  085005-1/54 ; Focus on Soft Mesoscopics : Physics for Biology at a Mesoscopic Scale

Fargier G., Favard C., Parmeggiani A., Sahuquet Q., Mérezègue F., Morel A., Denis M., Molinari N., Mangeat P.H., Coopman P.J., Montcourrier P.I. (2013) Centrosomal targeting of Syk kinase is controlled by its catalytic activity and depends on microtubules and the dynein motor, FASEB J. 27 109-122;

Neri I., Kern N., Parmeggiani A. (2013) Modelling intracellular traffic : an interplay between passive diffusion and active transport,Phys. Rev. Lett. Phys. Rev. Lett. 110. 098102;

Turci F., Parmeggiani  A., Pitard E., Romano  M. C., Ciandrini  L.,  (2013) Transport on a Lattice with Dynamical Defects, Phys. Rev. E 87. 012705-1/8

Innocentini G.C.P., Forger M., Ramos A.F., Radulescu O., Hornos J.E.M. (2013) Multi-modality and flexibility of stochastic gene expression. Bulletin of Mathematical Biology, 75:2600-30.

Noel V., Vakulenko S., Radulescu O.  (2013) A hybrid mammalian cell cycle model. Electronic Proceedings in Theoretical Computer Science - 125: 68-83.

Sen P., Vial H.J., Radulescu O. (2013) Kinetic modelling of phospholipid synthesis in Plasmodium knowlesi unravels crucial steps and relative importance of multiple pathways. BMC Systems Biology, 7:123.