项目名称: 基因调控网络重建的最优化模型与算法研究
项目编号: No.10801131
项目类型: 青年科学基金项目
立项/批准年度: 2009
项目学科: 生物科学
项目作者: 王勇
作者单位: 中国科学院数学与系统科学研究院
项目金额: 17万元
中文摘要: 细胞通过基因调控实现复杂的生命功能。利用微阵列基因表达数据构建基因调控网络是当前生物信息学和系统生物学的一个前沿研究热点。主要的挑战在于建立涉及成千上万变量的调控网络模型和克服生物实验产生的高噪声、相对缺乏的数据造成的病态多解现象。本研究计划中,我们将利用最优化方法来集成从不同尺度、角度、层面提供调控信息的异源生物数据,推断转录因子、基因、环境因素、化学小分子以及非编码RNA 之间的调控作用,并识别那些在不同条件下产生响应的信号通路。在方法论研究中,我们将根据实际问题和数据结构的特点在最优化建模中强调凸性和正则化项,以保证复杂生物问题的简化以及求解算法的高效。本项目的研究不仅可以为生物学家提供可靠的方法论和实用高效的工具软件,而且可以推动最优化理论和算法与生物分子网络和数据集成的交叉研究,加快国内系统生物学这一新兴交叉学科的发展。
中文关键词: 系统生物学;网络重建;数据集成;最优化;模型和算法
英文摘要: Cells utilize gene regulatory networks to perform complex functions. Thus reconstruction of gene regulatory network from microarray gene expression data has been a hot topic for the current bioinformatics and systems biology field. One of the major challenges is that a microarrays dataset consists of relatively few time points with respect to a large number of genes, which makes the problem of inferring gene regulatory network an ill-posed one. Here, we aim to develop new optimization methods to integrate heterogeneous data from different scales, sources, biological layers, to infer the regulatory relationships among transcription factors, target genes, environmental factors, chemical compounds, and non-coding RNAs, and to identify sigalling pathways or subnetwork in different conditions. From methodology aspect, we will emphasize the convexity and regularization in optimization models by fully considering the structures of practical problem and experimental data. In addition, we will simplify the complex biological problem and design effective and efficient algorithms. We believe that our studies will provide useful methodologies and software tools for biologist, boost the interdiscliplinary research by bridging optimization theory and algorithm with biomolecular network and data integration, and further to speed up the research on computational systems biology in China.
英文关键词: Systems Biology; Netowrk reconstruction;Data integration; Optimization; Model and algorithm