A Systems Biology Platform for Integrative Cancer Biology Research

描述(申请人提供)：肿瘤学研究中积累了浩瀚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中没有一个能够对这些数据进行全面处理和有意义的功能分析。在这里，我们建议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癌症领域知识结构化数据库和一个用于功能分析的工具包(本体丰富、互动组、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，我们开发了几种新的算法来对大型多患者数据集进行定量功能分析，并为不同类型的癌症数据集的交叉分析提供了新的方法。我们还设计了一个框架，用于手动注释癌症途径、分析和基因-疾病病因关联。在第二阶段，我们将把算法实现到一个健壮的“富客户端”分析平台上，并完成对癌症数据的注释。 公共卫生相关性：我们开发了用于不同类型数据集的定量功能分析和交叉分析的新算法。我们设计了一个框架，用于手动注释癌症途径、分析和其他数据。在第二阶段，我们将把算法实现到一个健壮的富客户端平台上，并完成注释程序

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