Application of Genomic Data in Translational Medicine During the Big Data Era.

Advances in gene sequencing technology and decreasing costs have resulted in a proliferation of genomic data as an integral component of big data. The availability of vast amounts of genomic data and more sophisticated genomic analysis techniques has facilitated the transition of genomics from the laboratory to clinical settings. More comprehensive and precise DNA sequencing empowers patients to address health issues at the molecular level, facilitating early diagnosis, timely intervention, and personalized healthcare management strategies. Further exploration of disease mechanisms through identification of associated genes may facilitate the discovery of therapeutic targets. The prediction of an individual's disease risk allows for improved stratification and personalized prevention measures. Given the vast amount of genomic data, artificial intelligence, as a burgeoning technology for data analysis, is poised to make a significant impact in genomics.
Competing Interests: The authors declare no conflict of interest. Given his/her role as Guest Editor, Feng Jiang had no involvement in the peer-review of this article and has no access to information regarding its peer review. Full responsibility for the editorial process for this article was delegated to Graham Pawelec.
(© 2024 The Author(s). Published by IMR Press.)