Systems biology and biological information processing

我的研究目标是研究复杂、动态的生物网络中出现的计算问题。我的很多研究都是由“高含量”技术推动的，比如体内表达成像或流式细胞术，在单细胞或组织中，以高空间和/或时间分辨率定量测量相对较少类型的分子的活性。我的研究主要集中在三个方面：(1)模型的建立和拟合，特别是空间/时间基因表达数据的建模和拟合；(2)实验设计，特别是时间序列实验和药物筛选问题；(3)生物分子系统信息处理能力的理论分析。在前两个重点中，我开发了一些技术，使我们能够最大限度地从分子生物学数据中获得信息量，并提高提取这些信息的效率。在最后的焦点中，目标是了解生物分子系统本身是如何做出决定的，或者它们如何被设计(通过“合成生物学”)来执行计算任务。

My research is targeted towards computational problems that arise in the study of complex, dynamic biological networks. Much of my research is motivated by "high-content" technologies, such as in vivo expression imaging or flow cytometry, in which the activities of a relatively small number of types of molecules are measured quantitatively with high spatial and/or temporal resolution in single cells or in tissues. My research focuses on three areas: (1) model formulation and fitting, particularly for spatial/temporal gene expression data, (2) experiment design, especially for time-series experiments and drug screening problems, and (3) theoretical analysis of the information processing capabilities of biomolecular systems. In the first two foci, I develop techniques that allow us to maximize the amount of information obtained from molecular biological data, and the efficiency with which that information is extracted. In the final focus, the goal is to understand how biomolecular systems themselves make decisions, or how they can be engineered (via "synthetic biology") to carry out computational tasks.