Section: Overall Objectives

Overall Objectives

This project aims at developing formal methods and experimental settings for understanding the cell machinery and establishing computational paradigms in cell biology. It is based on the vision of cells as machines, biochemical reaction networks as programs, and on the use of concepts and tools from computer science to master the complexity of cell processes.

This project addresses fundamental research issues in computer science on the interplay between structure and dynamics in large interaction networks, and on mixed analog-discrete computation. We contribute to the theory of biochemical computation, and develop since 2002 a modelling, analysis and synthesis software, the Biochemical Abstract Machine, BIOCHAM. The reaction rule-based language of this system allows us to reason about biochemical reaction networks at different levels of abstraction, in the stochastic, differential, discrete, Boolean and hybrid semantics of reaction networks. We develop a variety of static analysis methods before going to simulations and dynamical analyses. We use quantitative temporal logics as a mean to formalise biological behaviours with imprecise data and to constrain model building or network synthesis.

A tight integration between dry lab and wet lab efforts is also essential for the success of the project. This is achieved through tight collaborations with biologists and experimentalists. Furthermore, half of Lifeware is in the InBio group at Institut Pasteur headed by Grégory Batt who develops an experimental platform for the closed-loop control of intracellular processes. This platform combines hardware (microfluidic device and microscope), software (cell tracking and model-based predictive control algorithms) and liveware (genetically modified living cells). The originality of this project thus also deals with the recourse to advanced microscopy and synthetic biology technologies to perform accurate observations, modifications and real-time control at both single cell and cell population levels.

Because of the importance of optimization techniques in our research, we keep some activity purely dedicated to optimization problems, in particular on constraint programming methods for computing with partial information systems and solving NP-hard static analysis problems, and on continuous optimization methods for dealing with continuous parameters.