Know more

Our use of cookies

Cookies are a set of data stored on a user’s device when the user browses a web site. The data is in a file containing an ID number, the name of the server which deposited it and, in some cases, an expiry date. We use cookies to record information about your visit, language of preference, and other parameters on the site in order to optimise your next visit and make the site even more useful to you.

To improve your experience, we use cookies to store certain browsing information and provide secure navigation, and to collect statistics with a view to improve the site’s features. For a complete list of the cookies we use, download “Ghostery”, a free plug-in for browsers which can detect, and, in some cases, block cookies.

Ghostery is available here for free:

You can also visit the CNIL web site for instructions on how to configure your browser to manage cookie storage on your device.

In the case of third-party advertising cookies, you can also visit the following site:, offered by digital advertising professionals within the European Digital Advertising Alliance (EDAA). From the site, you can deny or accept the cookies used by advertising professionals who are members.

It is also possible to block certain third-party cookies directly via publishers:

Cookie type

Means of blocking

Analytical and performance cookies

Google Analytics

Targeted advertising cookies


The following types of cookies may be used on our websites:

Mandatory cookies

Functional cookies

Social media and advertising cookies

These cookies are needed to ensure the proper functioning of the site and cannot be disabled. They help ensure a secure connection and the basic availability of our website.

These cookies allow us to analyse site use in order to measure and optimise performance. They allow us to store your sign-in information and display the different components of our website in a more coherent way.

These cookies are used by advertising agencies such as Google and by social media sites such as LinkedIn and Facebook. Among other things, they allow pages to be shared on social media, the posting of comments, and the publication (on our site or elsewhere) of ads that reflect your centres of interest.

Our EZPublish content management system (CMS) uses CAS and PHP session cookies and the New Relic cookie for monitoring purposes (IP, response times).

These cookies are deleted at the end of the browsing session (when you log off or close your browser window)

Our EZPublish content management system (CMS) uses the XiTi cookie to measure traffic. Our service provider is AT Internet. This company stores data (IPs, date and time of access, length of the visit and pages viewed) for six months.

Our EZPublish content management system (CMS) does not use this type of cookie.

For more information about the cookies we use, contact INRA’s Data Protection Officer by email at or by post at:

24, chemin de Borde Rouge –Auzeville – CS52627
31326 Castanet Tolosan CEDEX - France

Dernière mise à jour : Mai 2018

Menu Logo Principal Logo BIA

Home page

Which proteins are hidden behind mass spectrometry spectra ?

donnees spectrométrie de masse
During the past few years, we have seen an increase in the technicality of our tools, with the constant evolution of our analytical capacity and a marked rise in the volume of data generated.

This evolution concerns, in particular, mass spectrometers used in proteomic studies for the identification, quantification and characterisation of the proteins found in organisms. In these studies, the analysis of unknown protein mixtures generates series of masses that constitute experimental spectra. Peptide interpretation of an experimental spectrum consists of comparing the experimental spectra to a set of ideal spectra (also referred to as theoretical spectra) extrapolated from the predicted fragmentation of proteins deduced from the genomic databases. Unfortunately, current software programmes used to interpret spectra are not sophisticated enough to interpret more than about 25% of spectra generated by an experiment.

Many parameters affect the behaviour of algorithms, including pretreatment of experimental spectra, the definition of the set of theoretical spectra compared to experimental spectra, and the score function that computes similarity between spectra. In order to assist the scientific community to better understand these parameters, we performed several distinct interpretations of the same experimental datasets with four software programmes including the ones most commonly used1. We showed that most of the software programmes give the same peptide interpretation for each spectrum when the set of theoretical spectra is strictly equal. In contrast, each software programme has its own score function to rank the spectra identifications, from the most to the least reliable. This ranking could have a great impact on the results, depending on the accepted error threshold.

A good understanding of algorithms and their limitations is also a prerequisite for the conception of new approaches that resolve their drawbacks. In addition to making the results of the comparison of four software programmes available to the scientific community, we also proposed innovative algorithms2 able to compare a large set (several tens of thousands) of experimental spectra with several hundreds of thousands of theoretical spectra in just a few minutes. This new approach identifies large sets of peptides that display post-translational modifications that cannot be detected by traditional software programmes. The development of a software programme to implement this new method is now being finalised.


Tessier, D., Lollier, V., Larré, C., and Rogniaux, H. (2016) Origin of Disagreements in Tandem Mass Spectra
Interpretation by Search Engines, J Proteome Res 15, 3481-3488.

David, M., Fertin, G., and Tessier, D. (2016). SpecTrees: An efficient without a priori data structure for
MS/MS spectra identification. In International Workshop on Algorithms in Bioinformatics, pages 65-76. Springer.