自噬是通过清除和回收溶酶体和液泡中受损的细胞器和细胞内成分来维持细胞稳态的关键保守细胞过程。自噬在细胞生存、生物能稳态、生物体发育和细胞死亡调节中发挥着至关重要的作用。自噬功能障碍与多种人类疾病和健康障碍有关，例如癌症和神经退行性疾病。自噬相关研究在基因、蛋白质、诊断等方面投入了大量精力。近年来，大量研究利用最先进的机器学习 (ML) 工具来分析和理解自噬的作用自噬在各种生物过程中的作用。我们对适用于自噬背景下的机器学习技术进行分类，全面回顾该路线的现有工作，并概述在生物医学背景下需要考虑的原则。为了认识到深度学习领域最近取得的突破性进展，我们讨论了跨学科合作的新机遇，并寻求让自噬和计算机科学研究人员共同努力促进自噬研究。版权所有 © 2024。由 Elsevier B.V. 出版。

Autophagy is a critical conserved cellular process in maintaining cellular homeostasis by clearing and recycling damaged organelles and intracellular components in lysosomes and vacuoles. Autophagy plays a vital role in cell survival, bioenergetic homeostasis, organism development, and cell death regulation. Malfunctions in autophagy are associated with various human diseases and health disorders, such as cancers and neurodegenerative diseases. Significant effort has been devoted to autophagy-related research in the context of genes, proteins, diagnosis, etc. In recent years, there has been a surge of studies utilizing state of the art machine learning (ML) tools to analyze and understand the roles of autophagy in various biological processes. We taxonomize ML techniques that are applicable in autophagy context, comprehensively review existing efforts in this route, and outline principles to consider in biomedical context. In recognition of recent groundbreaking advances in deep learning community, we discuss new opportunities in interdisciplinary collaborations and seek to engage autophagy and computer science researchers to promote autophagy research with joint efforts.Copyright © 2024. Published by Elsevier B.V.