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Review
. 2025 Jan 6:14:giaf057.
doi: 10.1093/gigascience/giaf057.

Artificial intelligence: the human response to approach the complexity of big data in biology

Giovanni Melandri  1   2 , Georges R-Radohery  1 , Chloé Beaumont  1 , Sara M de Cripan  3 , Coralie Muller  1   4 , Luca Piras  5 , Maria Alcina Pereira  6   7 , Andreia Ferreira Salvador  6   7 , Xavier Domingo-Almenara  3   8 , Marie Bolger  9 , Sophie Colombié  1   10 , Sylvain Prigent  1   10 , Biotza Gutierrez Arechederra  5 , Nuria Canela Canela  3 , Pierre Pétriacq  1   10
Affiliations
Review

Artificial intelligence: the human response to approach the complexity of big data in biology

Giovanni Melandri et al. Gigascience. .

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.

Keywords: artificial intelligence; biology; deep learning; life science; machine learning; omics.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1:
Figure 1:
Number of publications found in PubMed including [artificial intelligence] AND [omics] AND [life sciences] from 2004 to 2024. In total, 1,362 publications were found (19 September 2024). Considering the past 20 years, a literature search using the queries [omics] AND [artificial intelligence] AND [life sciences] confirms that AI in life sciences is a rapidly expanding field of research.
Figure 2:
Figure 2:
Data science in the era of artificial intelligence, machine learning and deep learning: a dynamic schematic breakdown.
Figure 3:
Figure 3:
Major approaches in machine learning and deep learning.
See this image and copyright information in PMC

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