A Systems Biology Platform for Integrative Cancer Biology Research

描述（由申请人提供）：肿瘤研究中正在积累大量的“小实验”数据和组学数据集，目前可用的生命科学信息学平台都无法对这些数据进行全面处理和有意义的功能分析。在这里，我们提出在我们成熟的数据分析平台MetaCore的基础上，构建这样一个系统——MetaMiner （Oncology）。该系统将拥有一个全面的结构化癌症领域知识数据库和一个用于功能分析的工具包（本体充实、交互组、网络工具）。MetaMiner将与CaBIG、转化医学数据库和第三方软件集成。在第一阶段，我们开发了几种用于大型多患者数据集定量功能分析的新算法，并为不同类型癌症数据集的交叉分析提供了新方法。我们还设计了一个框架，用于手动注释癌症途径、检测和基因-疾病病因关联。在第二阶段，我们将把这些算法实现为一个鲁棒的“富客户端”分析平台和完整的癌症数据注释。

DESCRIPTION (provided by applicant): A vast ocean of "small experiments" data and OMICs datasets is being accumulated in oncology research, and none of the currently available life sciences informatics platforms is capable of a comprehensive handling and meaningful functional analysis of these data. Here we propose to build such a system, MetaMiner (Oncology) on the base of our mature data analysis platform MetaCore. The system will have a comprehensive structured database of cancer domain knowledge and a toolkit for functional analysis (ontology enrichment, interactome, network tools). MetaMiner will be integrated with CaBIG, translational medicine databases and third party software. In Phase I, we developed several novel algorithms for quantitative functional analysis of large multi-patient datasets and offered new methods for cross-analysis of cancer datasets of different type. We have also designed a framework for manual annotation of cancer pathways, assays and gene-disease causative associations. In Phase II, we will implement the algorithms into a robust "rich client" analytical platform and complete annotation of cancer data. PUBLIC HEALTH RELEVANCE: We developed novel algorithms for quantitative functional analysis and cross-analysis of datasets of different type. We designed a framework for manual annotation of cancer pathways, assays and other data. In Phase II, we will implement the algorithms into a robust "rich client" platform and complete the annotation program