Genetic Regulatory Networks: Comp. & Ext. Investigations

描述（申请人提供）：生物学及其相关领域正在经历一场革命。定量方法和方法现在变得越来越普遍，很大程度上是由于测序技术和高通量基因组筛选方法的显著成就。其中一个主要的挑战是使用这些方法来理解基因的潜在机制和功能。本项目将采用的方法是对基因调控系统进行建模，并从基因表达数据中推断模型结构和参数。该项目的目标是进一步发展和完善数学和计算方法和模型，并将其应用于具体的生物模型系统。这不仅将作为建模方法的验证，而且还将导致对细胞功能和功能障碍的遗传调控机制的更好理解。具体目标是：1)比较不同的网络推理算法，并用实验方法对其进行验证；2)利用时序微阵列数据生成和评估子网络；3)预测和验证基因扰动对子网络中基因稳态表达的影响。该研究计划将紧密结合计算和实验方法来实现我们的目标。

DESCRIPTION (provided by applicant): Biology and related fields are currently witnessing a revolution. Quantitative approaches and methods are now becoming increasingly common, largely due to remarkable achievements in sequencing technologies and high-throughput genomic screening methods. One of the major challenges is to use such approaches for understanding the underlying mechanisms and functions of genes. The approach that will be taken in this project is to model the genetic regulatory system and infer the model structure and parameters from gene expression data. The goal of the project is to further develop and refine the mathematical and computational methods and models and to apply them to a concrete biological model system. This will not only serve as a validation of the modeling approach, but will also lead to an improved understanding of the genetic regulatory mechanisms underlying cellular function and dysfunction. In particular, the specific aims are 1) to compare different network inference algorithms and validate them with experimental methods; 2) to generate and evaluate sub-networks using time-course microarray data; 3) to predict and validate the effects of gene perturbations on steady-state expressions of genes in the sub-networks. The research program will closely integrate both computational and experimental approaches to achieve our goals.