Workshop on the BIOCHAM modeling environment

François Fages, Sylvain Soliman

Inria Saclay Ile-de-France


The Biochemical Abstract Machine (BIOCHAM) is a development environment for modeling, analyzing and synthesizing biochemical reaction networks (CRNs) in systems and synthetic biology. This workshop will be organized as a practical work where participants will use their own laptop to play with BIOCHAM notebooks on our server (without requiring any installation).

Content: BIOCHAM is essentially composed of:

  • An SBML-compatible language of formal reactions with rates (or influences with forces) which can be consistently interpreted in a hierarchy of differential (ODE), stochastic (CTMC), discrete (Petri net) and Boolean semantics.
  • A second language based on temporal logic used to specify the observed or desired behaviors of the system, either qualitatively (Computation Tree Logic CTL propositions) or quantitatively (first-order Linear Time Logic FO-LTL(Rlin) constraints)
  • Some unique features to enumerate the CTL properties of a CRN, compute parameter sensitivity indices, measure robustness and optimize parameter values w.r.t. FO-LTL(Rlin) specifications of the behavior, and synthesize CRNs.
  • A first notebook ( will be used to illustrate some basic concepts of BIOCHAM, through the example of a simple mitotic oscillator (after Goldbeter 1991 PNAS)

    You will also have the opportunity to develop your own notebook for analyzing or designing your favorite CRN (think about it in advance!).

    Audience: Scientists interested in modeling cell processes with concepts and tools from computer science and mathematics.

    Equipment: Participants should bring their laptop with an internet connection for connecting to BIOCHAM notebooks.


    0. user manual, tutorial notebook, etc.
    1. François Fages. Cells as Machines: towards Deciphering Biochemical Programs in the Cell (invited talk). In Proc. 10th International Conference on Distributed Computing and Internet Technology ICDCIT'14, pages 5067, volume 8337 of Lecture Notes in Computer Science. Springer-Verlag, 2014. [pdf]
    2. François Fages, Thierry Martinez, David Rosenblueth, Sylvain Soliman. Influence Networks compared with Reaction Networks: Semantics, Expressivity and Attractors. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018. [pdf]
    3. Aurélien Rizk, Grégory Batt, François Fages, Sylvain Soliman. Continuous Valuations of Temporal Logic Specifications with applications to Parameter Optimization and Robustness Measures. Theoretical Computer Science, 412(26):28272839, 2011. [pdf]
    4. François Fages, Steven Gay, Sylvain Soliman. Inferring Reaction Systems from Ordinary Differential Equations. Theoretical Computer Science, 599:6478, 2015. [pdf]
    5. Fages, François, Le Guludec, Guillaume and Bournez, Olivier, Pouly, Amaury. Strong Turing Completeness of Continuous Chemical Reaction Networks and Compilation of Mixed Analog-Digital Programs. In CMSB'17: Proceedings of the fiveteen international conference on Computational Methods in Systems Biology, pages 108127, volume 10545 of Lecture Notes in Computer Science. Springer-Verlag, 2017. [pdf]