Master 2 course C2-19 Biochemical Programming

Master Parisien de Recherche en Informatique University Paris Diderot, UPMC, Paris-Saclay, X, ENS (pedagogical server)

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.

• the slides will be available below at https://lifeware.inria.fr/wiki/Fages/BiochemicalProgramming
• the TP are not graded, they are just proposed to you as a mean to practice the taught concepts
• bibliography:
  • chapitre de livre facile à lire La cellule, un calculateur analogique chimique 2020
  • lecture notes 2017

Tentative schedule 2025:

20 Jan 2025 12.455-15.45 room 1004

• Introduction to Chemical Reaction Networks (CRNs) pdf
  • TP Lotka-Volterra CRN (online Jupyter notebook of BIOCHAM)
• Abstract interpretation of CRNs: hierarchy of semantics, typings pdf

27 Jan. room 1004

• Moment closures pdf
  • TP Stochastic genetic switch
• Turing completeness of continuous CRNs pdf
  • TP synthetic oscillators
  • TP chemical arithmetic

3 Feb.

• Quasi-steady state approximation pdf Δ
  • TP Michaelis-Menten reduction
• Formalizing behaviours in quantitative temporal logic, model verification, robustness, optimization pdf Δ
  • TP robustness optimization in MAPK signaling network
  • TP doctor in the cell

10 Feb.

• Computation Tree Logic, CRN model-checking pdf Δ
  • TP MAPK model-checking
• Probably Approximately Correct Learning pdf Δ
  • TP PAC learning
  • TP PAC learning

17 Feb.

• Break

24 Feb, 3 March: break? exam?

• Written examination of both parts of the course (50%-50% grade)
• Every electronic device disallowed
• Any printed document allowed

Previous written examinations with solutions:

• March 2024 subject (solution given here by Biocham)
• March 2023 subject (solution given here by Biocham)
• March 2022
• (March 2021 programming/modeling project)
• March 2020
• March 2019
• (March 2018 programming/modeling project)
• Feb 2017
• Nov 2015 (plus March 2016 programming/modeling project)
• Feb 2015
• Mar. 2014
• Mar. 2013
• Mar. 2012
• Feb. 2011
• Nov. 2009
• Nov. 2008
• Nov. 2007
• Nov. 2006.