Section: Application Domains

Computational Systems Biology

In partnership with biologists, we develop and experiment our modeling methods in five main leading applications:

• Cancer chronotherapy optimization. This research initiated in 2004 in partnership with Jean Clairambault, EPI BANG, and Francis Lévi INSERM, Hopital Paul Brousse, Villejuif, aims at understanding fundamental mechanisms involved in cancer and chronotherapies through mathematical modeling. Following the EU STREP project TEMPO (2006-2009) on “temporal genomics for patient tailored chronotherapeutics”, coordinated by Francis Lévi, and in the framework of the Era-Net SysBio C5Sys project (2010-2013) coordinated by Francis Lévi and David Rand, University of Warwick, UK, we develop coupled models of the cell cycle, the circadian clock, the DNA repair system, irinotecan metabolism and drug injection optimization, focussing on the interactions between the cell cycle and the circadian clock in mammalian cells.

• Mammalian cell cycle regulation. This theme that is closely related to the previous one has lead to a formal collaboration in the framework of the ANR Syscomm project CALAMAR , started in 2009 on the “Compositional modeling and Analysis of LArge MoleculAr Regulatory networks”. In partnership with Claudine Chaouiya, TAGC INSERM, Marseille, and Laurence Calzone, Institut Curie, Paris, this project aims at applying our computational techniques – both qualitative and quantitative – to the analysis of the large scale RB/E2F network, in order to elucidate various features of the human cell proliferation, especially in the case of healthy and bladder-tumor cells of different aggressiveness.

• Real-time control of gene expression in yeast. This research lead in the team by Grégory Batt investigates the possibilities to control gene expression in living cells. In collaboration with Pascal Hersen and Samuel Bottani, biophysicists at the Matière and Systèmes Complexes lab, CNRS/Paris Diderot University, we develop a microfluidic platform and control software for the real-time control of gene expression in yeast. In a larger initiative, we consider a similar problem but in mammalian cells, where the stochasticity of gene expression makes the control problem particularly challenging. The Iceberg Investissement d'Avenir project, coordinated by Grégory Batt, involves the MSC, BM2A, LIFL and PPS labs, and the Jacques Monod Institut. Similarly, the Contraintes research group is also involved in the Inria/INSERM large-scale initiative action COLAGE coordinated by Huges Berry, EPI COMBINING, with François Taddei, Ariel Lindner, INSERM Paris Necker, Hidde de Jong, Delphine Ropers, EPI IBIS, Jean-Luc Gouzé, and Madalena Chaves, EPI COMORE. In this project, we investigate the possibilities to control and reprogram growth and aging in bacteria E. coli using synthetic biology approaches.

• Artificial tissue homeostasis in mammalian cells. Artificial tissue design is a particularly challenging problem in synthetic biology since the system behavior results from the interplay between intra- and intercellular dynamics. In the framework of the Syne2arti ANR project, coordinated by Grégory Batt, and involving Dirk Draso, EPI BANG, Oded Maler, CNRS Verimag, and Ron Weiss, MIT, USA, we design and genetically-engineer mammalian cells to obtain a tissue having a desired cell density. The long-term correct functioning of the system relies several key aspects, including individual cell decisions, collective, spatial aspects, and cell-to-cell variability.

• TGF$\beta$ signaling In the framework of the BioTempo ANR project, we recently started to apply the different algorithms available in the BIOCHAM platform to the modeling of the TGF$\beta$ signaling network in collaboration with the SeRAIC lab (Rennes, France). The main challenge is to compare and understand crosstalks between the SMAD-dependent fast pathway and the MAPK-dependent slower pathway that is often related to cancer. Both the static network analyzers and the parameter learning methods of BIOCHAM are put to good use in this work.