Genetic networks: Dynamics, inference, analysis and evolution

遗传网络可以看作是活细胞的控制系统。基因之间的调控关系是分子生物学的基本问题之一。测量生物分子丰度和它们之间相互作用的技术的进步，为解决这一问题提供了革命性的新数据，产生了单个基因的详细图像，以及基因活性和相互作用的细胞范围快照。然而，数据的数量和其中的不确定性，需要新的计算方法来提取有意义的信息。我研究的总体目标是推进高通量分子生物学数据分析的理论和实践，最终提供足够高效和强大的数学和计算工具，成为分子生物学家标准分析工具包的一部分。我的工作将主要集中在三个方面：(1)发展理论和算法来推断基因之间的调节关系，特别是微分方程模型。(2)将建模方法应用于重要的生物系统。(3)开发功能解释和遗传网络工具。

Genetic networks can be viewed as the control systems of living cells. Inferring regulatory relationships between genes, which implement this control system, is one of the fundamental problems in molecular biology. Advances in technologies for measuring the abundances of biomolecules, and interactions between them, are providing revolutionary new data for solving this problem, yielding detailed pictures of individual genes as well as cell-wide snapshots of gene activity and interactions. However, the quantity of the data, and uncertainties in it, necessitate new computational approaches for extracting meaningful information. The overall goal of my research is to advance both the theory and practice of the analysis of high-throughput molecular biology data, ultimately providing mathematical and computational tools that are efficient and robust enough to become part of the standard analysis toolkit of molecular biologists. My efforts will focus primarily in three areas: (1) Developing theory and algorithms for inferring regulatory relationships between genes, particularly differential equation models. (2) Applying modeling methods to important biological systems. (3) Developing tools for the functional interpretation and genetic networks.