predict and quantify the mechanistic effect of treatments and the role of master regulators

model and simulate multi-level system characterization


a partner asked COSBI to quantify the combined effect of the C677T MTHFR variant and vitamin B6 level on the one-carbon metabolism


by developing proprietary modeling and simulation techniques, we encoded the one-carbon pathway into a graphical model for both deterministic and stochastic simulation

proprietary software

COSBI developed a novel graphical language to model biological systems and novel stochastic and hybrid algorithms to speed up simulation




a biological interpretation of the simulation led us to quantify the combined effect of C677T MTHFR variant and vitamin B6 deficiency on SAM-SAH ratio


C. Uluseker, G. Simoni, L. Marchetti, M. Dauriz, A. Matone, C. Priami. A closed-loop multi-level model of glucose homeostasis. PloS ONE, 13 (2): e0190627, 2018.

L. Marchetti, V.H. Thanh, C. Priami. Simulation algorithms for computational systems biology. In Texts in Theoretical Computer Science. An EATCS Series, Springer, ISBN: 978-3-319-63111-0, 2017.
K. Misselbeck, L. Marchetti, M.S. Field, M. Scotti, C. Priami and P.J. Stover. A hybrid stochastic model of folate-mediated one-carbon metabolism: Effect of the common C677T MTHFR variant on de novo thymidylate biosynthesis. Nat. Sci. Rep., 7:797, 2017.

H. Vo Thanh, R. Zunino, C. Priami. Accelerating Rejection-based Simulation of Biochemical Reactions with Bounded Acceptance Probability, Journal of Chemical Physics, 144, 2016.

L. Marchetti, C. Priami, H. Vo Thanh. HRSSA - Efficient Hybrid Stochastic Simulation for Spatially Homogeneous Biochemical Reaction Networks. Journal of Computational Physics, 317:301-317, 2016.

C. Priami and M.J. Morine. analysis of biological systems. Imperial College Press, 2015

F. Capuani, A. Conte, E. Argenzio, L. Marchetti, C. Priami, S. Polo, P.P. Di Fiore, S. Sigismund, A. Ciliberto. Quantitative analysis reveals how EGFR activation and downregulation are coupled in normal but not in cancer cells. Nat. Comm., 6:799, 08/2015

H. Vo Thanh, R. Zunino, C. Priami. On the Rejection-based Algorithm for Simulation and Analysis of Large-Scale Reaction Networks. Journal of Chemical Physics, 142:244106, 2015, doi: 10.1063/1.4922923

S. Rizzetto, C. Priami, A. Csikàsz-Nagy. Qualitative and Quantitative Protein Complex Prediction Through Proteome-Wide Simulations. PLOS Comp. Biol., 11:10, e1004424, (2015)

R. Gostner, B. Baldacci, M.J. Morine, C. Priami Graphical Modelling Tools for Systems Biology. ACM Computing Surveys, 47(2), 2014

O. Karamanogullari, P. Lecca, D. Morpurgo, G. Fantaccini, C. Priami. Algorithmic modeling quantifies the complementary contribution of metabolic inhibitions to gemcitabine efficacy. PloS ONE, 7:12, 2012

M.L. Guerriero, A. Dudka, N. Underhill-Day, J.K. Heath, C. Priami. Narrative-based computational modelling of the Gp130/JAK/STAT signalling pathway. BMC Systems Biology, 3:40, 2009

C. Priami. Algorithmic Systems Biology. Communication of the ACM, 52(5):80-88, May 2009

L. Dematté, C. Priami, A. Romanel. The Beta Workbench: a computational tool to study the dynamics of biological systems. Briefings in Bioinformatics, 9(5): 437-449, 2008

D. D’Ambrosio, P. Lecca, G. Constantin, C. Priami, C. Laudanna. Concurrency in Leukocyte Vascular Recognition: Developing the Tools for a Predictive Computer Model. Trends in Immunology, 25(8):411-416, 2004

P. Lecca, C. Priami, C. Laudanna and G. Constantin. Computer modeling of lymphocyte behavior in inflamed brain venules by using stochastic π-calculus. Journal of Neuroimmunology, 154(1-2):230-230, 2004

C. Priami, A. Regev, E. Shapiro and W. Silvermann. Application of a stochastic name-passing calculus to representation and simulation of molecular processes. Information Processing Letters, 80: 25-31, 2001

C. Priami. Stochastic π-calculus. The Computer Journal, 38(6):578-589, 1995.