The Era of Large-Scale Data in Biological Sciences

We are living in the era of large-scale data in the biological sciences. The completion of the Human Genome Project (HGP) marked a pivotal moment, not only for its monumental achievement but also for introducing the concept of Big Science to the life sciences. This project catalysed a technological revolution, shifting biology from a primarily descriptive and hypothesis-driven discipline to a data-intensive, interdisciplinary field capable of systematic and quantitative exploration of biological systems at an unprecedented scale.This new paradigm is embodied by omics approaches, defined as experimental methods based on technologies that enable the systematic, qualitative, quantitative, and unbiased characterization of all molecular components of a given type within a biological system, or the interactions between them. From genomics and transcriptomics to proteomics and metabolomics, these technologies have moved us from studying individual molecules to capturing global views of biological processes. This has been fundamental for the emergence of Systems Biology, a unifying approach that seeks to understand complex biological systems by identifying their components and interactions and predicting systems behaviour through mathematical and computational models.In this chapter we provide an overview of the rise of the "-omes" and their corresponding omics approaches, their conceptual foundations, and the implications they carry for research in the life sciences, including controversies, challenges, and opportunities. We conclude by discussing how the convergence of omics and artificial intelligence is reshaping the epistemological foundations of biological research, bridging data accumulation and inference of molecular mechanisms.