Digital biology to understand and predict biological systems


HepatO'Twin © Julos, Freepik

18 June 2024

By: Marjorie Domergue

HepatO’Twin: a digital twin to investigate the effects of food contaminants on the hepatic metabolism

The HepatO'twin project will put the concept of the digital twin to use in exploring the effects of food contaminants on the liver’s metabolism. This will allow us to advance understanding of the contribution made by diet and exposure to food contaminants to the risk of developing metabolic diseases.
InsiliCow DiGIT-BIO, © INRAE
By applying the concept of the digital twin at the scale of a dairy farm, the inSiliCow project will develop a multi-scale simulation tool to aid on-farm decision-making with regard to farming practices for dairy cows. The inSiliCow project is a flagship ‘digital twin’ project for the Metaprogramme DIGIT-BIO.
Booklet of projects DIGIT-BIO
Since its launch in March 2021, DIGIT-BIO has funded 6 interdisciplinary consortia and 14 exploratory projects in the field of digital biology. Find an overview of the actions supported by the metaprogramme.
Illustration adn
in the nucleus of a cell, the three-dimensional conformation of the genome has a major impact on how it functions. A better understanding of the links between the 3D structure of the genome and its functioning represents a methodological challenge and requires dialogue between different disciplines

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".


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