title:
Biochemical Programming
Programmation biochimique
manager:
François Fages
ects:
3
period:
2
hours:
24
weeks:
8
hours-per-week:
3
language:
French by default
lang:
track:
C
themes:
Bio-info, Parallel/Distributed Algo., Semantic/Languages, Verification
number:
2.19
year:
2025, 2026
  • Biochemical Programming
    Programmation biochimique
  • Language:
  • Period:
  • 2.
  • Duration:
  • 24h (3h/week).
  • ECTS:
  • 3.
  • Manager:
  • François Fages.

Biochemical Programming (24h, 3 ECTS)

Coordinator: François Fages.

Teachers in 2025-2026

Aims

Over the past two decades, formal methods from Theoretical Computer Science have been successfully applied in Life Sciences to decipher biological processes, mostly at the molecular and cellular levels.

This course aims at presenting these methods and research issues in computational systems biology and synthetic biology. It is based on the vision of

cells as machines,

biochemical reaction systems as programs

and on the use of concepts and tools from Computer Science to master the complexity of cell processes.

Unlike most programs, biochemical computation involves state transitions that are stochastic rather than deterministic, continuous-time rather than discrete-time, poorly localized in compartments instead of well-structured in modules, and created by evolution instead of by rational design.

The course addresses fundamental research issues in Computer Science about the interplay between structure and dynamics in large interaction networks, and on the mixed continuous (analog) and discrete (digital) computation model of biochemical networks.

Evaluation

The evaluation is composed of one written examination (and sometimes of one modelling/programming project). Previous exams are available on teachers' pages (see the course handouts section below). For the written examination, any printed documents are allowed, any electronic devices are disallowed.

Course outline

1. Protein interaction calculus (Jérôme Féret, 12h)

  • Introduction to biological models and rule-based modeling in the Kappa-calculus
  • Scalable stochastic simulation algorithm, introduction to the KaSim tool.
  • Theoretical computer science techniques applied to bio modeling: causality analysis, static analysis.
  • Model reduction.

2. Chemical reaction networks (CRN) as a programming language (François Fages, 12h)

  • Introduction to the Biochemical Abstract Machine tool Biocham-4
  • Hierarchy of CRN semantics: differential (ODE), stochastic (CTMC), discrete (Petri net), Boolean
  • Turing completeness of continuous CRNs: chemical compilation of mixed analog/digital programs
  • Specifying behaviours in (quantitative) temporal logic: model-checking and model synthesis

Course handouts

Course handouts can be found here:

French and English

The lectures will be given in English upon request. All slides, documents and the examination subjects will be in English.

Related courses

2.11.1 Approximation Algorithms & molecular programming 2.06.1 Abstract interpretation 2.29.1 Graph algorithms 2.35.1 Constraint programming 2.03.1 Concurrency

Prerequisites

Knowledge in formal methods in computer science and in differential calculus are useful but not a prerequisite.

There is no prerequisite in Biology, the basics of cell biology will be introduced as needed through examples all along the course.

Pedagogic team

F. Fages DR Inria Saclay
J. Féret CR CNRS ENS

Tentative calendar

On Wednesdays 16.15-19.15 room 1002

Dec 10 JF 1
Dec 17 JF 2
Dec 23 - Jan 5 Christmas vacations
Jan 7 JF 3
Jan 14 JF 4
Jan 21 FF 1
Jan 28 FF 2
Feb 4 FF 3
Feb 11 FF 4
Feb 18 Break
Feb 25 Break
Mar 3 or 11 Written Examination
Any electronic devices disallowed
Any printed documents allowed

Bibliography

  • Rule Based Modelling of Cellular Signalling. V. Danos, J. Feret, W. Fontana, R. Harmer and J. Krivine. Proceedings of CONCUR’07 : 18th International Conference on concurrency theory. Springer-Verlag, LNCS 4703, 2007.
  • Artificial Intelligence in Biological Modeling. F. Fages. In A Guided Tour of Artificial Intelligence Research. Springer-Verlag, to appear. ( pdf)
  • Cells as Machines: towards Deciphering Biochemical Programs in the Cell. F. Fages and S. Soliman. In Proc. 10th International Conference on Distributed Computing and Internet Technology ICDCIT'14, pages 50–67, volume 8337 of Lecture Notes in Computer Science. Springer-Verlag, 2014. ( pdf)
  • Formal cell biology in BIOCHAM. F. Fages and S. Soliman, 8th International School on Formal Methods for the Design of Computer, Communication and Software Systems: Computational Systems Biology, Springer-Verlag, LNCS 5016, 2008. ( pdf)
  • Synthetic biology: New engineering rules for an emerging discipline. E. Andrianantoandro, S. Basu, D. Karig, and R. Weiss, Molecular Systems Biology, 2006.

Previous years

Some former students of this course who continued for a PhD Thesis or a Post-Doc in Computational Systems Biology:

  • 2004-2005: Jean Krivine, PhD Inria Rocquencourt, now CNRS Paris-Diderot
  • 2004-2005: Colas Le Guernic, PhD CNRS Grenoble, then New York University
  • 2005-2006: Sylvain Pradalier, PhD Inria Rocquencourt, now Dassault-Systèmes
  • 2005-2006: Fabien Tharissan, now MdC UPMC
  • 2006-2007: Aurélien Rizk, PhD Inria Rocquencourt, then Paul Sherrer Institute Zurich, Co-Founder&CTO InterAx Biotech
  • 2008-2009: Steven Gay, PhD Inria Rocquencourt, now Google Paris
  • 2008-2009: Laurent Bulteau, PhD Univ. Nantes
  • 2011-2012: Guillaume Madelaine, PhD Univ. Lille
  • 2013-2014: Andrea Beica, PhD ENS Paris
  • 2014-2015: Virgile Andreani, PhD Inria Saclay, then Pasteur Institute, now Inria Saclay
  • 2015-2016: Guillaume Le Guludec, course project followed by internship at Inria Saclay then best paper award CMSB 2017, Prix La Recherche magazine 2019
  • 2016-2017: Arthur Carcano, PhD Inria Paris, Pasteur Institute
  • 2016-2017: Theotime Grohens, PhD Inria Lyon
  • 2018-2019: Martin Larralde, EMBL Heidelberg
  • …
  • 2024-2025: Hélène Siboulet, Inria Saclay