摘要
脂肪细胞分化是一个由基因和通路驱动的生物学过程,对能量代谢至关重要。但基因网络的复杂性、细胞异质性及多尺度数据整合的挑战,限制其机制研究和转化进展。人工智能(artificial intelligence,AI)技术,特别是机器学习和深度学习,通过分析大型数据集、预测分化阶段和解码调控机制推动该领域研究。本研究总结AI在脂肪细胞数据及图像处理、分化预测、互作网络分析、肥胖研究和药物发现方面的应用,并探讨当前挑战和未来发展方向。
Adipocyte differentiation is a gene and pathway-driven biological process critical to energy metabolism.However,the complexity of gene networks,cellular heterogeneity,and challenges in multi-scale data integration have limited mechanistic studies and translational progress.Artificial intelligence(AI)technologies,particularly machine learning and deep learning,have driven research in this field by analyzing large datasets,predicting differentiation stages,and decoding regulatory mechanisms.This study summarizes AI applications in adipocyte data and image processing,differentiation prediction,interaction network analysis,obesity research,and drug discovery,while exploring current challenges and future research directions.
作者
高辉
陈彩霞
GAO Hui;CHEN Caixia(Department of Thoracic Surgery,Inner Mongolia Hospital of Peking University Cancer Hospital(Affiliated Cancer Hospital of Inner Mongolia Medical University),Hohhot 010020,Inner Mongolia,China;Central Laboratory of Affiliated Hospitals,Inner Mongolia Medical University,Key Laboratory of Cell Biology Inner Mongolia,Hohhot 010050,Inner Mongolia,China;School of Life Sciences,Inner Mongolia Agricultural University,Hohhot 010018,Inner Mongolia,China)
出处
《中国现代医生》
2025年第35期55-59,共5页
China Modern Doctor
关键词
脂肪细胞分化
人工智能
机器学习
深度学习
肥胖
Adipocyte differentiation
Artificial intelligence
Machine learning
Deep learning
Obesity
