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LIFEWARE Research team

Computational systems biology and optimization

Team presentation

The project Lifeware 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 on the interplay between structure and dynamics in large interaction networks, and on mixed analog-digital computation. A tight integration between dry lab and wet lab efforts is also essential for the success of the project. In collaboration with biologists, we investigate concrete biological questions and develop computational models fitted to quantitative data which allow us to make quantitative predictions, revisit biological knowledge, and design artificial biochemical circuits.

Research themes

- Biochemical programming: theory, compilation, natural and synthetic programs - Model reduction: structural and quantitative methods - Artificial tissue design: long--term dynamics and dynamical structures - Real-time control of intracellular processes - Combinatorial and continuous optimization methods

International and industrial relations

Lifeware has tight collaborations with Jie-Hong Jiang (National Taiwan University, Taiwan) on biochemical programming, with Francis Lévi (Univ. Warwick, UK), with Thomas Sturm (MPI Saarbrucken, Germany) and Andreas Weber (Bonn University, Germany) on symbolic computation methods for model reduction, and with Lingchong You (Duke University, USA) on cell population models. Lifeware also had a long time collaboration with Dassault-Systèmes on computational methods in systems biology for the pharma industry and is currently developing a new collaboration with Servier.

Keywords: Computational systems biology Computational modeling Chemical programming Formal methods Synthetic biology Optimization