Non exhaustive list of research subjects for Ph.D. theses, Post docs, or internships at different levels. If you are a motivated talented student with your own subject on topics relate to LIFEWARE, or for any question on the subjects below, please contact by email François Fages.


Ph.D. theses and PostDoc positions in LIFEWARE


No demand yet, but don't hesitate to contact us if you have a research subject to propose to us in connection with our project.


Research Internships for Masters and Engineering Schools (with possible continuation for a Ph.D. Thesis)


Hybrid differential-stochastic simulation (research internship, 6-3 months)


Boolean SATisfiability modulo Differential Equations for verifying chemical reaction networks (research internship, 6-3 months)


Visualisation of biochemical reaction networks using static analyzers (research internship, 6-3 months)


Research Initiation Internships for L3, M1 and Engineering school students:


Visualisation of biochemical reaction networks using static analyzers (research internship, 6-3 months)

> Benchmarking modern ODE integration methods for biochemical reaction networks

Contact: Sylvain Soliman

Currently the Biocham v4 [2] modellng software uses the GNU Scientific Library as go-to method for integrating ODE systems corresponding to the time-evolution of biochemical networks. Biocham v3 used a (Prolog) hand-coded version of some Rosenbrock method.

As is now common knowledge in the ODE-integration community [1] GSL is quite bad at this task and some more recent methods might do much better either for stiff or non-stiff systems.

Using the above blog post as reference, a benchmark of those recent methods, mostly those available through the Sundials library, notably the recent ARKODE, on real dynamical systems coming from Systems Biology publications, would be a huge improvement for the Biocham suite. It is currently not known how often the considered systems are stiff or semi-stiff, how often they use events, etc.

The results would be directly added to the Biocham suite [2] and might result in a tool-article.

Benchmarking des méthodes modernes d'intégration d'EDOs pour les réseaux biochimiques

Contact: Sylvain Soliman

À l'heure actuelle, l'outil Biocham v4 [2] utilise GNU Scientific Library comme source générique de méthodes d'intégration de systèmes d'équations différentielles correspondant à l'évolution de réseaux biochimiques. Biocham v3 utilisait une méthode de Rosenbrock implémentée en interne (en Prolog).

Il est désormais bien connu de la communauté d'intégration d'EDOs [1] que GSL est un assez mauvais choix et que des méthodes plus récentes seraient bien plus efficaces dans le cas de systèmes stiffs comme non-stiffs.

En partant de l'article de blog ci-dessus comme référence, le stage consistera à évaluer les méthodes récentes, notamment celles disponibles dans la bibliothèque Sundials, et en particulier ARKODE, sur des systèmes dynamiques réels provenant de publications en Biologie Systémique. Cela permettra une amélioration sensible de la suite Biocham [2] dans laquelle les résultats seraient immédiatement intégrés. Par exemple, on ne sait pas aujourd'hui quelle proportion de ces systèmes sont stiffs ou semi-stiffs, lesquels utilisent des évènements, etc.

Une publication sous forme d'article-outil est envisagée.

References:

[1] http://www.stochasticlifestyle.com/comparison-differential-equation-solver-suites-matlab-r-julia-python-c-fortran/

[2] Biocham http://lifeware.inria.fr/biocham/