SCREEN:predicting single-cell gene expression perturbation responses via optimal transport

作     者：Haixin WANG Yunhan WANG Qun JIANG Yan ZHANG Shengquan CHEN Haixin WANG;Yunhan WANG;Qun JIANG;Yan ZHANG;Shengquan CHEN

作者机构：Cadre Medical DepartmentThe 1st Clinical CenterChinese PLA General HospitalBeijing 100853China School of StatisticsRenmin University of ChinaBeijing 100872China Ministry of Education Key Laboratory of BioinformaticsBioinformatics Division of BNRISTDepartment of AutomationTsinghua UniversityBeijing 100084China School of Mathematical Sciences and LPMCNankai UniversityTianjin 300071China 

出 版 物：《Frontiers of Computer Science》 (中国计算机科学前沿（英文版）)

年 卷 期：2024年第18卷第3期

页      面：255-257页

核心收录：

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China(Grant No.62203236) the Fundamental Research Funds for the Central Universities,Nankai University(63231137) 

主　　题：stimulation perturbation deepening 

摘      要：1 Introduction Recent advances in single-cell RNA sequencing(scRNA-seq)have enabled the study of how individual cells respond to various external perturbations such as drug stimulation at gene expression level[1].Precisely inferring perturbation responses allows us to explore how and why individual tumor cells evade cancer treatment,greatly advancing personalized medicine research and deepening our understanding of biological mechanisms[2].However,considering the high costs of sequencing and the complexity of obtaining perturbed samples,utilizing computational methods to predict cellular responses to perturbations holds great potential[2].