I am a researcher at the CNRS (Centre National de la Recherche Scientifique). I work at the Centre de Biophysique Moléculaire in Orléans and as an associate researcher at the Synchrotron SOLEIL.

Research interests

My two main current fields of research are

  • The structure and dynamics of proteins, using molecular simulation and statistical physics. Much of my work is method development, in particular in the field of Elastic Network Models.
  • The methodology of computational science, in particular concerning reproducibility and digital scientific notations in the context of the Open Science movement.


My most up-to-date publication list is available from HAL, which also has the full text of my recent publications (preprints or final, depending on the journal).

For less structured and totally non-peer-reviewed thoughts on various topics concerning today's scientific research, see my digital garden on Science in the digital era.

Editorial activity

I am a member of the editorial board of the IEEE magazine Computing in Science and Engineering, where I am in charge of the Scientific Programming department.

I am also one of the editors-in-chief of ReScience, an on-line journal dedicated to publishing replications of previously published computational studies.


Most of my teaching is about scientific computing and centered around reproducible research. This is in particular the topic of a MOOC that I have been working on with several colleagues.

Software development

As a method developer I do a lot of software development for my research, and I make all of this software available as Open Source code. I was one of the first scientists to adopt the Python language in 1994, and most of my software is written in Python.

In 1996, I was a founding member of the Matrix-SIG that created Numerical Python, the predecessor to today's NumPy. In 1997 I published ScientificPython, one of the first Python libraries for scientific computing (and unrelated to the younger SciPy library).

My most widely used software is the Molecular Modelling Toolkit, a Python library for molecular simulations, first published in 1997. It is used mainly by scientists developing new simulation and analysis methods, but also for developing end-user applications. If you use Chimera or nMOLDYN, to name but two examples, you are also using MMTK, perhaps without being aware of it.

Two more recent projects, ActivePapers and MOSAIC, combine research with software development with the goal of making (bio)molecular simulation more reproducible.

Another step towards more trustworthy computational science is my digital scientific notation project Leibniz. It will permit writing down computational models as distinct entities from software that implements them. Such explicitly represented models can be analyzed, compared, and discussed in the scientific literature, and also become part of formal specifications for scientific software.