GigaScience, 14 (2025)
by Giovanni Melandri, Georges R-Radohery, Pierre Pétriacq, Chloé Beaumont, Sara M de Cripan, Coralie Muller, Sophie Colombié, Sylvain Prigent (University of Bordeaux), Luca Piras, Xavier Domingo-Almenara, Biotza Gutierrez Arechederra, Nuria Canela Canela (Eurecat), Maria Alcina Pereira, Andreia Ferreira Salvador (University of Minho) & Marie Bolger (Institute of Bio- and Geosciences, IBG-4)
Abstract
Since the late 2010s, artificial intelligence (AI), encompassing machine learning and propelled by deep learning, has transformed life science research. It has become a crucial tool for advancing the computational analysis of biological processes, the discovery of natural products, and the study of ecosystem dynamics. This review explores how the rapid increase in high-throughput omics data acquisition has driven the need for AI-based analysis in life sciences, with a particular focus on plant sciences, animal sciences, and microbiology. We highlight the role of omics-based predictive analytics in systems biology and innovative AI-based analytical approaches for gaining deeper insights into complex biological systems. Finally, we discuss the importance of FAIR (findable, accessible, interoperable, reusable) principles for omics data, as well as the future challenges and opportunities presented by the increasing use of AI in life sciences.
