Amity Institute of Biotechnology, Amity University Jharkhand, Ranchi, India.
Amity Institute of Organic Agriculture, Amity University, Noida, India.
OMICS. 2023 Dec;27(12):550-569. doi: 10.1089/omi.2023.0197.
With climate emergency, COVID-19, and the rise of planetary health scholarship, the binary of human and ecosystem health has been deeply challenged. The interdependence of human and nonhuman animal health is increasingly acknowledged and paving the way for new frontiers in integrative biology. The convergence of genomics in health, bioinformatics, agriculture, and artificial intelligence (AI) has ushered in a new era of possibilities and applications. However, the sheer volume of genomic/multiomics big data generated also presents formidable sociotechnical challenges in extracting meaningful biological, planetary health and ecological insights. Over the past few years, AI-guided bioinformatics has emerged as a powerful tool for managing, analyzing, and interpreting complex biological datasets. The advances in AI, particularly in machine learning and deep learning, have been transforming the fields of genomics, planetary health, and agriculture. This article aims to unpack and explore the formidable range of possibilities and challenges that result from such transdisciplinary integration, and emphasizes its radically transformative potential for human and ecosystem health. The integration of these disciplines is also driving significant advancements in precision medicine and personalized health care. This presents an unprecedented opportunity to deepen our understanding of complex biological systems and advance the well-being of all life in planetary ecosystems. Notwithstanding in mind its sociotechnical, ethical, and critical policy challenges, the integration of genomics, multiomics, planetary health, and agriculture with AI-guided bioinformatics opens up vast opportunities for transnational collaborative efforts, data sharing, analysis, valorization, and interdisciplinary innovations in life sciences and integrative biology.
随着气候紧急情况、COVID-19 疫情以及行星健康学术研究的兴起,人类健康和生态系统健康的二分法受到了深刻挑战。人类健康和非人类动物健康的相互依存关系越来越得到认可,并为综合生物学的新前沿铺平了道路。健康、生物信息学、农业和人工智能 (AI) 领域的基因组学融合带来了一个新时代的可能性和应用。然而,大量生成的基因组/多组学大数据也在提取有意义的生物学、行星健康和生态洞察方面带来了严峻的社会技术挑战。在过去的几年中,人工智能引导的生物信息学已成为管理、分析和解释复杂生物数据集的强大工具。人工智能的进步,特别是机器学习和深度学习,正在改变基因组学、行星健康和农业领域。本文旨在剖析和探讨这种跨学科整合所带来的广泛可能性和挑战,并强调其对人类和生态系统健康的根本变革潜力。这些学科的整合也在推动精准医学和个性化医疗保健方面取得重大进展。这为我们深入了解复杂的生物系统并促进行星生态系统中所有生命的健康提供了前所未有的机会。尽管需要考虑其社会技术、伦理和关键政策挑战,但将基因组学、多组学、行星健康和农业与人工智能引导的生物信息学相结合,为生命科学和综合生物学领域的跨国合作努力、数据共享、分析、增值和跨学科创新开辟了广阔的机会。