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


Not yet available


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


Soon available


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


> Static analyses for biochemical reaction network visualization

Contact: François Fages

In the domain of computational systems biology, biochemical reaction diagrams are a central medium of communication between biologists and modellers. Unfortunately in this context, automatic graph visualization tools such as GraphViz [1] do not produce well-organized diagrams, and manual edition tools such as Cell Designers are preferred.

The purpose of this internship is to explore the use of static analyzers of reaction networks to extract information relevant to the "logical" drawing of biochemical reaction networks. More specifically, we propose to explore the use of the static analyzers of our modeling software, the Biochemical Abstract Machine (Biocham) [2], to design placement constraints for tools like GraphViz. For instance, the computation of linear conservation laws (i.e. Petri net P-invariants [3]) in Biocham provide information on groups of molecules that are transformed but conserved under their different forms and that could be preferably drawn on the same line. The use of dynamic analyzers, e.g. relying on numerical simulation, will be considered also if necessary [3].

References:

[1] GraphViz http://www.graphviz.org

[2] Biocham v4 http://lifeware.inria.fr/biocham/

[3] François Fages. AI in Biological Modeling. To appear in A Guided Tour of Artificial Intelligence Research. Springer-Verlag, 2017. preprint

> 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/