DIGIT-BIO metaprogramme

DIGIT-BIO

Digital biology to understand and predict biological systems

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@Olivier FILANGI
article

29 June 2026

By: Marjorie Domergue

Contextualization of plant metabolomics data using knowledge graphs enhanced by Big Data, AI and Semantic Web technologies

The SEED project expands the Metabolomic Semantic Data Lake (MSD), an electronic infrastructure that combines the Semantic Web with Big Data technologies to enable large-scale processing of the scientific literature on metabolomics. First developed to improve access to knowledge on the links between the metabolism and human health, this infrastructure has now been adapted to include plant metabolisms. SEED will refine its use of artificial intelligence, enabling publications to be annotated automatically through the use of ontologies. The project will also expand the range of sources included in the data lake and will draw on four case studies to validate and illustrate the new associations discovered between metabolites, biomarkers and plants.
Photo d'un puceron © wirestock, Freepik

The pressures exerted on plants by insect pests such as aphids are increasing, as are the viral diseases they carry. The changing climate, reduced insecticide use and the development of resistance to those pesticides that are still authorized have all conspired to boost the life cycle and population dynamics of these pests. With the need to reduce insecticide use, new agro-ecological approaches have emerged in recent decades that use crop genetic diversity as a tool to modify aphid behaviors or performance. To be effective, such approaches require the accurate characterization of plant genetic diversity, yet there is currently no open, high-performance, standardized and affordable phenotyping system available to developers of future applications. The aim of the Gratitude consortium is to fill this gap by developing a digital plant-aphid system that can characterize aphid development and behavior.

Illustration thèse confinancée

Thesis by Julien Kossi Kowou (2025 - , UMR GABI). This PhD project aims to develop statistical analysis methods to explore inter-species genetic diversity.

Thesis by Adèle Coppel (2025 - 2028, LIPME). The objective of this PhD project is to investigate, through modelling approaches, the role of wind in the modulation of plant immune responses and to identify molecular actors involved in the variability of resistance associated with acclimation and sensitization.

Our goals

The quantitative and qualitative explosion of data in biology, combined with the development of new tools for processing and analysing these data, is revolutionising research in the life sciences. This development opens up new perspectives for better understanding the functioning of biological systems and predicting their behaviour.

The metaprogramme Digit-Bio aim to support research at the interface between computational / engineering sciences and life sciences (biology, physics, chemistry or environmental sciences), in order to:

  • Understand the functioning and predict the behaviour of biological systems
  • Anticipate the impact of stresses on these systems, reason out their management and develop levers for action.  In the medium term, the ambition is to develop a small number of projects for in silico monitoring of biological systems, based on the concept of the "digital twin".

 

Axis schématic DIGIT-BIO © INRAE
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