Department of Life Sciences, Pohang University of Science and Technology, Pohang 37673, Korea.
Graduate School of Artificial Intelligence, Pohang University of Science and Technology, Pohang 37673, Korea.
BMB Rep. 2023 Jan;56(1):43-48. doi: 10.5483/BMBRep.2022-0155.
Pre-clinical models are critical in gaining mechanistic and biological insights into disease progression. Recently, patient-derived organoid models have been developed to facilitate our understanding of disease development and to improve the discovery of therapeutic options by faithfully recapitulating in vivo tissues or organs. As technological developments of organoid models are rapidly growing, computational methods are gaining attention in organoid researchers to improve the ability to systematically analyze experimental results. In this review, we summarize the recent advances in organoid models to recapitulate human diseases and computational advancements to analyze experimental results from organoids. [BMB Reports 2023; 56(1): 43-48].
临床前模型对于深入了解疾病进展的机制和生物学特性至关重要。最近，患者来源的类器官模型的发展有助于我们理解疾病的发展，并通过真实地再现体内组织或器官来改善治疗方案的发现。随着类器官模型技术的快速发展，计算方法在类器官研究人员中受到关注，以提高系统地分析实验结果的能力。在这篇综述中，我们总结了类器官模型在再现人类疾病方面的最新进展，以及用于分析类器官实验结果的计算方法的最新进展。[BMB 报告 2023;56(1):43-48]。
