DNA sequencing has revolutionized biological and biomedical research, offering profound insights into genome organization, function, and variability. From the pioneering Sanger capillary electrophoresis method to the advent of next-generation sequencing, the field has evolved toward unprecedented speed, scalability, and cost decreases over the years. These advancements have enabled diverse applications across genomics, transcriptomics, metagenomics, epigenomics, and precision medicine, powering global initiatives such as the Human Genome Project, the Human Microbiome Project, and the 1000 Genomes Project. Bioinformatics has also advanced in data processing, variant detection, and functional annotation, helping transform raw sequencing data into biologically meaningful insights and knowledge. Although highly advanced, sequencing technologies still encounter challenges, including accuracy trade-offs and the need for efficient management of rapidly increasing volumes of data. Leveraging the genomic revolution, this review explores the shifts toward next-generation phenomics (NGP), an archetype that uses artificial intelligence that integrates multi-omics data with digital phenotyping, the Internet of Things, and real-time analytics. The goal of NGP is to integrate genotypic and phenotypic data to support predictive modeling of health, disease, and environmental interactions. By tracing history, advances in sequencing technologies, and future perspectives on NGP, this article offers a comprehensive overview for researchers and clinicians, highlighting how the integration of omics and digital data will drive the generation of personalized and systems-level biology.
Ranga et al. (Mon,) studied this question.