生物医学大数据发展的新挑战与趋势

he bio-medical data has entered a new era from exabyte-scale of genomic data to petabyte-scale of multi-dimensional big data, transforming the biological and medical research into a data-intensive science that is also referred as the fourth paradigm of discovery. Such transformation presented a set of new challenges: we have to efficiently gather and share high-dimensional and multi-level clinical and research data, further facilitate the comprehensive utilization of various omics data, clinical data, and phenome data of large population, eventually convert big data to new knowledge. Such challenges have to be faced by employing a new series of paradigm shifting ideas. In particular, new frameworks should be developed to improve the current submission-based data storage system to an integration-oriented system; to improve the subjective-based data sharing system to an interactive-oriented system; to integrate the cutting edge information technologies into the current data mining system. At the same time, large efforts have to be invested in developing data standardization guidelines and quality control technologies. These ideas will be critical in order to establish next generation of bio-medical big data centers and will be a new trend of future research.