Big data: Historic advances and emerging trends in biomedical research

Abstract

• Big data is achieving remarkable results and transforming biomedical research. • Big data from multi-omics technologies is advancing medicine and healthcare. • Multi-omics, and meta- and co-expression analyses play key roles in big data integration for better understanding of human diseases. • Actionable measures (e.g., policies, funding and interdisciplinary collaborations) may pave the way to innovative biomedical breakthroughs. Big data is transforming biomedical research by integrating massive amounts of data from laboratory experiments, clinical investigations, healthcare records, and the internet of things. Specifically, the increasing rate at which information is obtained from omics technologies (genomics, epigenomics, transcriptomics, proteomics, metabolomics, and pharmacogenomics) is providing an opportunity for future advances in personalized medicine that are paving the way to improved patient care. The recent advances in omics technologies are profoundly contributing to big data in biomedicine and are anticipated to aid in disease diagnosis and patient care management. Herein, we critically review the major computational techniques, algorithms, and their outcomes that have contributed to recent advances in big data generated from biomedical research in various complex human diseases, such as cancer and infectious diseases. Finally, we discuss trends in the field and the future directions that must be considered to advance the influence of big data on biomedical research and its translation in the healthcare industry.