The Pasteur Museum is housed in the apartment where Louis Pasteur spent his final seven years and offers a rare behind-the-scenes look at the living and working environment of the world-renowned scientist. Visitors can gain a unique insight into his everyday life alongside his wife and can admire his rich and diverse scientific work.
The Institut Pasteur’s scientific strategy focuses on developing original and innovative topics and promoting interdisciplinary and multidisciplinary cooperation and approaches. The Institut Pasteur teams have access to the technological resources needed to speed up and further improve the quality of their outstanding research.
Ever since the introduction of the world’s first "Technical Microbiology" course in 1889, teaching has been a priority for the Institut Pasteur. The Institut Pasteur has an international reputation for quality teaching that attracts students from all over the world who come to further their training or top up their degree programs.
The mission of the Industrial Partnership team is to detect, promote, assist and protect the inventive activities from research (inventions, know-how and biological materials) conducted at the Institut Pasteur (and in some Institutes of its international network), and transfer there to industrial and/or institutional partners, in order to serve the patient needs and for the benefit of the society, as well as to contribute to sustainability of the Institut Pasteur’s resources.
With international courses, PhD and postdoctoral traineeship, each institute of the Institut Pasteur International Network (RIIP) contributes to the transmission of knowledge with the training of young researchers all around the world. In this context, doctoral and postdoctoral programmes, study and traineeship fellowships are available to scientists. Alongside training, dynamism and attractiveness of RIIP will result in the creation of 4-year group for the young researchers.
Statistical and Mathematical Modeling in Biological Applications
The seminar series Statistical and Mathematical Modeling in Biological Applications (SaMMBA) features monthly lectures and discussions with leading modelers in biological sciences. Presentations are in English or French and target an interdisciplinary audience. Seminars are held on the campus of Institut Pasteur. Access is free. However, to enter the campus, one needs a badge that is obtained at the main gate in exchange of a piece of ID (passport, citizen card or driver licence).
Abstract: Approximate Bayesian computation is a method used to handle intractable likelihoods, for instance in population genetics, where it was introduced in the late 1990's. The choice of the summary statistics used in Bayesian inference and in particular in ABC algorithms has severe bearings on the validation of the resulting inference. Those statistics are nonetheless customarily used in ABC algorithms without consistency checks. We derive necessary and sufficient conditions on summary statistics for the corresponding Bayes factor to be convergent, namely to asymptotically select the true model. Those conditions, which amount to the expectations of the summary statistics to asymptotically differ under both models, are quite natural and can be exploited in ABC settings to infer whether or not a choice of summary statistics is appropriate, via a Monte Carlo validation. We will also discuss substitutes to automated summary statistic selection toward model choice, based on the machine learning technique of random forests.