IMR Press / FBL / Volume 29 / Issue 1 / DOI: 10.31083/j.fbl2901007
Open Access Review
Application of Genomic Data in Translational Medicine During the Big Data Era
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1 Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, 210029 Nanjing, Jiangsu, China
2 Department of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, 200090 Shanghai, China
*Correspondence: chuyan_w@hotmail.com (Chuyan Wu); dxyjiang@163.com (Feng Jiang)
Front. Biosci. (Landmark Ed) 2024, 29(1), 7; https://doi.org/10.31083/j.fbl2901007
Submitted: 9 May 2023 | Revised: 3 September 2023 | Accepted: 7 September 2023 | Published: 12 January 2024
Copyright: © 2024 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.
Abstract

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.

Keywords
genomic data
translational medicine
next-generation sequencing
whole-genome association studies
polygenic risk scores
machine learning
Funding
82172539/National Natural Science Foundation of China
JSPH-MC-2022-19/Jiangsu Province Hospital (the First Affiliated Hospital with Nanjing Medical University) Clinical Capacity Enhancement Project
Figures
Fig. 1.
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