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 AgroParisTech Université Paris-Saclay


GABI : Génétique Animale et Biologie IntégrativeUnité Mixte de Recherche INRA - AgroParisTech

PREDICT research strategy initiative: Predictive Biology for health

PREDICT research strategy initiative: Predictive Biology for Health
PREDICT is a research initiative coordinated by SAPS units (Sciences Animales Paris-Saclay), supported by the Life Sciences Department of the University Paris-Saclay. This initiative which is both multidisciplinary and multi-community includes research teams working in the animal sciences, plant sciences, medical research, fundamental biology and infectiology, biostatistics and modeling, ethics and law. PREDICT provides an environment for research and discussion to promote actions in the field of predication for health. It is part of a societal approach with support from the House of Human and Social Sciences of the Paris-Saclay University.

MOTS-CLES : Predictive Biology - multidisciplinary networks- 1Health - Life Sciences - Human and Social Sciences - Biostatistics - Biomarkers - Data Integration - Genomics - circulating microRNA

Predictive Medicine reknews therapeutic practices. It is being deployed, in particular, thanks to the massive acquisition of biological behavioral and sociological data, making it possible to make predictions based on genomic and environmental information.

These approaches for health are also at the heart of research currently being led in animals and plants, with the shared objective of favoring resistance to pathogens and environmental stress factors while reducing the use of antibiotics and phytosanitary products in order to promote the ecological transition in agriculture.

Within a scientific and socio-econmic context where health research is still largely being performed in silos, decompartmentalization wishes have emerged. The One Health initiative (One World, One Health), which is aimed at associating research in human and animal health in relation with the environment, is emblematic of this approach. The anchoring of INRA research teams in the University Paris-Saclay has created original opportunities on the theme of predictive biology for health, with the possibility of comparing medicine and precision farming. PREDICT is an offshoot. 

Three complementary actions have been proposed:
  1. create scientific animation at the interface of the life, human and social sciences;
  2. develop a methodological network for the analysis of heterogenous and complex data for predictive modeling;
  3. develop robust and sensitive methods for the large-scale detection of circulating miRNA in biological fluids for their use as biomarkers in man, animals and plants.
Amongst the results:
  • publication of the proceedings of a conference prepared in relation with the House of Human and Social Sciences of Paris-Saclay on the theme, "Predictive approaches for health: cross-referencing the socio-economic and scientific issues in humans, animals and plants".
  • two workshops for data analysis whose programs and presentations are available on-line. Over one-hundred scientists participated in the workshop held at Jouy-en-Josas on "Heterogenous and high-throughput data integration for the discovery of predictive markers". A second workshop "Deep learning and genomics" held at INRA Versailles gathered approximately 200 participants, reflecting the interest for methods associated with neuron networks, which today are experiencing an upsurge of interest with "Deep Learning" applied to massive amounts of data.
  • comparison of different methodological approaches for the detection of circulating miRNA located in human, animal and plant biological fluids and the identification of the most sensitive and reliable method (nine teams contributing from the University Paris-Saclay).

The ineractions with the SHS Paris-Saclay communities reinforce the opportunites for interdisciplinary projects. The challenge of associating teams that study animals, plants and man has given us the chance to decompartmentalize the thematic silos, in particular on the shared questions of global health (one's health depends on the health of others).

The methodological network for the multi-scale analysis and integration of data has joined the PsayCompBio network led by a scientist of Paris-Sud, favoring a long term dynamics of computational biology, at the interface between applied mathematics, bioinformatics and biology.

The methodological network on multispecies detection of biomarkers in biological fluids will be organizing a restitution seminar in February, 2019.


Main correspondant:

Other INRA contacts:

Associated Division: Génétique Animale

Associated research center: Jouy-en-josas

INRA priority of the Guidance Document



#OpenScience-3 : Predictive approaches in Biology