基于高通量RNA-Seq和多目标协同演化模因计算的疾病模块识别研究

项目名称： 基于高通量RNA-Seq和多目标协同演化模因计算的疾病模块识别研究

项目编号： No.61471246

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 无线电电子学、电信技术

项目作者： 朱泽轩

作者单位： 深圳大学

项目金额： 80万元

中文摘要： 高通量RNA-Seq正在成为基因表达研究的主要工具,基于RNA-Seq数据构建基因组共表达网络对于发现疾病模块揭示疾病内部复杂分子机制有重要意义，但由于RNA-Seq的大数据量和高分辨率特性，专门针对其设计的高效共表达网络构建和疾病模块识别方法还非常匮乏。本课题针对重要疾病的RNA-Seq数据，提出核典型关联分析和全局间接相关静默技术相结合的基因共表达网络构建方法，并针对构建网络提出基于多目标协同演化模因计算的疾病模块识别方法。重点解决RNA-Seq数据压缩存取、基于外显子表达水平的基因共表达关系衡量、带权基因组共表达网络构建、多目标网络模块度定义、大规模协同演化分组、多层次局部搜索、集成聚类和疾病模块有效性评估等具体问题，实现针对RNA-Seq数据的高效通用疾病模块识别系统。项目开展有助于提高疾病基因预测水平及对复杂疾病内部分子机制的认识，可为RNA-Seq数据的系统分析提供借鉴。

中文关键词： 智能计算；进化算法；多目标优化；复杂网络；基因表达

英文摘要： High-throughput RNA-Seq is becoming the major tool to study gene expression. Reconstruction of genomic co-expression network is pivotal to disease modules identification as well as revealing the underlying interaction mechanism of moleculars. However, due to the large data volume and high resolution nature of RNA-Seq, new efficient gene co-expression network reconstruction and disease modules identification methods oriented to RNA-Seq data are required. In this project, a novel gene co-expression network reconstruction method based on kernel canonical correlation analysis and global indirect correlation silencing technique is proposed toward RNA-Seq data of important diseases. The successive disease modules identification proceeds based on a multiobjective cooperative coevolutionary memetic computing framework. Particularly, the research effort is focused on addressing the compressive storage and access of RNA-Seq data, the evaluation of exon level gene expression correlation, the reconstruction of weighted genomic co-expression network, the definition of multiobjective fitness function, the grouping strategy in large-scale cooperative coevolution, the design of multilevel local search, the ensemble clustering, and the disease modules validation. The outcomes of the project are expected to improve the prediction of disease genes and the understanding of the underlying mechanism of diseases, and provide insight into the system analysis of RNA-Seq data.

英文关键词： Computational Intelligence;Evolutionary Algorithm;Multiobjective Optimization;Complex Network;Gene Expression