Next generation causal inference methods for biological data

该项目旨在开发下一代因果推理方法，用于分析生物数据，特别是单细胞测序数据及其在细胞生物学中的应用。虽然人工智能和统计机器学习已经在包括生物学研究在内的许多领域得到了成功的应用，但仍然严重缺乏对生物系统的机制进行解释和推理的方法，这是许多领域研究的最终目标。该项目开发的高效数据驱动的因果关系发现方法将对生物学和统计学知识以及与健康威胁作斗争作出及时和重大的贡献。

This project aims to develop next generation causal inference methods for analysing biological data especially the single cell sequencing data and their applications in cell biology. Although Artificial Intelligence and Statistical Machine Learning have been applied successfully in many fields, including biological research, there is still a serious lack of methods for interpreting and reasoning about the mechanism of biological systems, the ultimate goal of research in many areas. Efficient data-driven causality discovery approaches developed by the project will be a timely and significant contribution to the knowledge of biology and statistics as well as the battle against health threats.