Developing Informatics Technologies to Model Cancer Gene Regulation

开发信息学技术来模拟癌症基因调控

• 批准号: 8606997
• 负责人: Xiaole Shirley Liu
• 金额: $ 36.31万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-17 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8606997
• 关键词: Abbreviations; Address; Algorithms; Binding; Biological; Blast Cell; ChIP-seq; Chromatin; Collaborations; Communities; Computational algorithm; Computer software; Data; Data Analyses; Data Collection; Data Quality; Data Set; Databases; Deoxyribonucleases; Development; Dictionary; Disease; Epigenetic Process; Feedback; Galaxy; Gene Expression; Gene Expression Regulation; Gene Targeting; Genes; Genetic Transcription; Genomics; Imagery; Informatics; Internet; Logic; Malignant Neoplasms; Maps; Metadata; Methods; Modeling; Molecular; Molecular Profiling; Monte Carlo Method; Mutate; Oncogenes; Positioning Attribute; Process; Public Domains; Published Comment; Publishing; Quality Control; Records; Regulation; Research; Research Infrastructure; Resource Informatics; Resources; System; Techniques; Technology; The Cancer Genome Atlas; Trans-Activators; Transcription Coactivator; Work; acronyms; anticancer research; base; combinatorial; computerized data processing; data integration; data sharing; design; epigenome; experience; flexibility; genome wide association study; genome-wide; improved; innovation; insight; interoperability; novel; open source; outreach; programs; public health relevance; repository; research study; software development; software systems; statistics; tool; transcription factor; tumorigenesis

Project Summary / Abstract Genome-wide studies have demonstrated that trans-acting factors, including transcription factors, chromatin regulators and other chromatin-associated factors, are frequently mutated in cancer, reaffirming that aberrant gene regulation is a key mechanism in oncogenesis. The way in which these trans-acting factors regulate transcription on a genome-wide basis is poorly understood, motiving ever increasing number of ChIP-seq and DNase-seq experiments to map genome-wide transcription factor binding (cistrome) and chromatin status (epigenome). Novel and significant biological insights have been gained through the analysis of ChIP-seq and DNase-seq data integrated with other published ChIP-seq and DNase-seq data sets as well as expression profiles. Most cancer biologists, however, find computational data analysis and integration of cistrome and epigenome data to be the major bottleneck of such studies due to the lack of informatics expertise and infrastructure. The objective of this proposal is to develop the informatics technologies to improve the acquisition, analysis, integration and reuse of ChIP-seq and DNase-seq data so as to allow experimental cancer biologists to model transcriptional and epigenetic gene regulation in cancer research. Specifically, we propose to develop informatics technologies to address three critical aspects of epigenome and cistrome data analysis. First, we will implement software to automate data collection, processing and quality control, enabling diverse types of unpublished and public ChIP-seq and DNase-seq data to be analyzed and converted into statistics and formats that can be readily used for integrative analysis. Second, we will develop systems to allow gene expression data to be interpreted with cistrome and epigenome data in order to elucidate regulatory mechanisms. Third, we will develop tools to quickly and accurately identify informative public datasets and to infer combinatorial rules of regulation and interactions. Finally, we will develop the infrastructure and interface to host the algorithms and tools developed in the first three aims, and provide the experimental cancer biologists with a flexible and intuitive user experience. We will design our software to interact easily with complementary software systems and databases. The software developed in this proposal will be freely available open-source, and we will work with our collaborators and users to improve its functions and user interface.

项目概要/摘要 全基因组研究表明，反式作用因子，包括转录因子、染色质 调节因子和其他染色质相关因子在癌症中经常发生突变，这再次证实了异常 基因调控是肿瘤发生的关键机制。这些反式作用因子的调节方式 对全基因组基础上的转录知之甚少，这促使 ChIP-seq 和 DNase-seq 实验绘制全基因组转录因子结合（顺反组）和染色质状态 （表观基因组）。通过 ChIP-seq 的分析获得了新颖且重要的生物学见解 DNase-seq 数据与其他已发布的 ChIP-seq 和 DNase-seq 数据集以及表达集成 配置文件。然而，大多数癌症生物学家发现顺反组和顺反组的计算数据分析和整合 由于缺乏信息学专业知识，表观基因组数据成为此类研究的主要瓶颈 基础设施。该提案的目标是开发信息技术以改善 ChIP-seq 和 DNase-seq 数据的采集、分析、集成和重用，以便 实验癌症生物学家模拟癌症中的转录和表观遗传基因调控 研究。 具体来说，我们建议开发信息学技术来解决以下三个关键方面： 表观基因组和顺反组数据分析。首先，我们将实施软件来自动化数据收集， 处理和质量控制，支持多种类型的未发表和公共 ChIP-seq 和 DNase-seq 数据进行分析并转换为易于使用的统计数据和格式 综合分析。其次，我们将开发系统来允许基因表达数据 用顺反组和表观基因组数据进行解释，以阐明调控机制。第三，我们 将开发工具来快速准确地识别信息丰富的公共数据集并推断 调节和相互作用的组合规则。最后，我们将发展基础设施和 托管前三个目标中开发的算法和工具的接口，并提供 实验癌症生物学家提供灵活直观的用户体验。我们将设计我们的 与互补软件系统和数据库轻松交互的软件。软件 本提案中开发的内容将免费开放源代码，我们将与我们的合作 合作者和用户改进其功能和用户界面。