基于新一代测序数据的基因调控网络数学模型与方法的研究

项目名称： 基于新一代测序数据的基因调控网络数学模型与方法的研究

项目编号： No.11201460

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 数理科学和化学

项目作者： 万林

作者单位： 中国科学院数学与系统科学研究院

项目金额： 22万元

中文摘要： 新一代测序技术在现代生物学和医学研究中得到广泛应用。随着前期数据处理的数学与计算方法的基本完善，如何进一步分析和挖掘新一代测序数据，深入研究基因调控网络，成为了当前研究的热点与难点。针对新一代测序数据的自身问题及其提供的基因调控的关键信息，本项目将致力于发展基于新一代测序数据的基因调控网络的数学模型和方法，特别是概率统计的模型和方法，着重解决三个方面的关键问题：（1）基于模型的新一代测序数据系统偏差的校正，（2）基于等位基因特异性表达机制与模型的基因调控网络的因果推断，以及（3）基于RNA降解模型的基因调控动态网络的研究等。本项目将为系统生物学和生物信息学领域提供新的研究方法，并将推进我们对人类复杂疾病的基因调控机制的深入理解与研究。

中文关键词： 新一代测序数据；基因调控网络；空间混杂校正；动态网络分析；系统生物学

英文摘要： The emerging next generation sequencing (NGS) technologies have been widely employed in biological and biomedical studies. With the huge amount of data being generated, the processing and analysis of NGS data raises lots of mathematical and computational challenges. As new mathematical and computational methods have been successfully developed to handle these difficulties in data processing, we are now moving to the next stage of the downstream analysis with the goal to deepen our understanding of the biology, especially the gene regulatory networks (GRNs) based on the NGS data. Currently, however, most existing methods of GRNs were developed based on the microarray data rather than the NGS data, making them not applicable to the NGS-based studies. To fill this gap, our project will develop new mathematical models and methods, especially the probabilistic and statistical models and methods, for the NGS-based GRN studies. Specifically, the project will study the following three key scientific questions, (1) the model based bias adjustment methods for the NGS data; (2) the causal inference of the GRNs based on the modeling of allele-specific expression; and (3) the study of the dynamic GRNs by considering RNA degradation. This project will not only provide new methodologies for the studies of systems biology and b

英文关键词： Next Generation Sequencing Data；Gene Regulatory Networks；Spatial Crosstalk Adjustment；Dynamic Networks Analysis；Systems Biology