Dr Josselin Noirel

Downloads: 1. Heuristic method to analyse proteomic data (software, modules [1,2], see Noirel et al., Briefings in Functional Genomics and Proteomics, March 2008). Documentation will be made available soon. 2. R implementation of MMG: MMG package (submitted to Bioinformatics — see also Sanguinetti et al., Bioinformatics, 8(24):1078–1084).

I have been working as a postdoctoral researcher in Pr Phillip Wright's group since March 2007. I am interested in the insights provided by mapping quantitative proteomic data onto metabolic networks. The rationale behind this is merely that the organisms are selected for responding in an adapted, efficient fashion to a condition change. It is therefore reasonable to think that the metabolic processes are co-ordinated and synchronised in order to make the metabolic fluxes efficiently react to such a change. If this is true, a consistent behaviour should be observed along the metabolic pathways, or in other words, the metabolic scaffold should convey some information on the correlation between various measurements. Because proteomic data are sparse, there are many uncertainties, but the metabolic structure may be useful in order for us to infer a given enzyme's response (up- or down-regulated, unchanged?). Such an approach is useful in compiling, in analysing the results, as well as in suggesting routes of further investigation. — Another aspect of my research is to apply this methodology to the understanding of the mechanisms involved in the hydrogen production in Cyanobacterias.

PhD: In silico evolution of monomeric and dimeric proteins. École polytechnique, supervised by Pr T. Simonson. In French, available from the university's website.