CORE 3: Bioinformatics

核心3：生物信息学

• 批准号: 9278479
• 负责人: IVAN P GORLOV
• 金额: $ 20.39万
• 依托单位: UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9278479
• 关键词: American Joint Committee on Cancer; Area; Atlases; Base Sequence; Bioinformatics; Biological Process; Biology; Clinical; Clinical Markers; Data; Data Analyses; Database Management Systems; Databases; Diagnosis; Encyclopedias; Ensure; Environmental Exposure; Etiology; Gene Expression; Gene Expression Profiling; Generations; Genes; Genetic; Genetic Polymorphism; Genotype-Tissue Expression Project; Germ-Line Mutation; Goals; Grant; Human; Individual; Knowledge; Medical Genetics; Methylation; MicroRNAs; Modeling; Molecular; Mutation; Neoplasm Metastasis; Online Systems; Outcome; Participant; Pathway interactions; Patients; Policies; Process; Prognostic Marker; Proteins; Publishing; Regulation; Research; Research Personnel; Research Project Grants; Sampling; Secure; Somatic Mutation; Source; Survival Rate; Survivors; System; Systems Integration; TNM; Testing; The Cancer Genome Atlas; Time; United States National Institutes of Health; Validation; actionable mutation; analytical tool; base; clinical biomarkers; comparative; computerized data processing; data integration; data management; data sharing; differential expression; feeding; insight; mRNA Expression; melanoma; melanoma biomarkers; molecular marker; molecular subtypes; novel; outcome forecast; outcome prediction; predictive marker; prognostic; programs; response; survival outcome; targeted treatment; transcription factor; tumor; whole genome

SUMMARY CORE 3 The goal of Bioinformatics core is to provide data management and bioinformatics support in a timely and efficient manner. The core will process, and analyze the data derived from P01 projects and provide bioinformatics support and expertise to the projects. We propose 3 objectives. The first objective will be to provide management, storage and sharing of the data. We will build a database to allow researchers to select samples and data tailored to specific questions. The database will be used as a platform for data analysis and integration. The second objective is to provide analytical support for the first 3 research projects. We will help to identify drivers mutations associated with melanoma progression. We will also provide a comprehensive extended (upstream regulators and downstream targets) annotation of the top hits (project 1). Whole genome methylation analysis (project 2) is expected, like all other research projects, to generate multiple hits across multiple regions. We developed powerful analytical tool that allows identification of the set of transcription factors whose downstream effects will be impeded by abnormal methylation. We will also provide bioinformatics support for gene expression analysis (project 3). We will construct regulatory network of the genes differentially expressed in long- term (>5 years) versus short-term (<5 years) bad survivors. We will provide comprehensive annotations of differentially expressed genes with the goal of the identification of molecular pathways associated with metastatic progression. Our third objective will be to provide bioinformatics support for data integration (project 4). We see two levels of integration: integration between the projects of the P01 and integration with the data and results generated outside if the P01. The first level of integration will be based on the assumption that melanoma progression is driven by a modulation of a single or a few biological functions and those functions can be modified by different mechanisms: germline and somatic mutations, modulation of the gene expression through genetic and somatic polymorphisms, methylation, and environmental exposures. We expect to find a stronger overlap between the results generated by different projects on the level of biological functions than on the gene level. Melanoma has been a hot research area and a lot of data and results related to the melanoma progression have been generated. We will combine the data generated by this P01 with TCGA, GEO, GTEx, ONCOMINE, Human Protein Atlas and other public sources. Using data from outside sources will allow us to test and refine key findings from this P01.

核心3摘要 生物信息学核心的目标是提供数据管理和生物信息学支持， 及时和有效的方式。核心将处理和分析来自P01项目的数据 并为项目提供生物信息学支持和专业知识。我们提出三个目标。的 第一个目标是提供数据的管理、储存和分享。新的起点上建设更加富裕 数据库，使研究人员能够选择样本和数据量身定制的具体问题。的 数据库将用作数据分析和整合的平台。第二个目标是 为前三个研究项目提供分析支持。我们将帮助识别司机 与黑素瘤进展相关的突变。我们还将提供全面的 最高命中的扩展（上游调节子和下游靶）注释（项目1）。 全基因组甲基化分析（项目2）预计，像所有其他研究项目， 在多个区域产生多个命中。我们开发了强大的分析工具， 鉴定其下游作用将被以下阻碍的转录因子组： 异常甲基化我们还将为基因表达分析提供生物信息学支持 （项目3）。我们将构建长-中差异表达基因的调控网络， 长期（>5年）与短期（<5年）不良生存者。我们将提供全面的 差异表达基因的注释，目的是鉴定 与转移进展相关的途径。我们的第三个目标是提供 对数据整合的生物信息学支持（项目4）。我们看到两个层次的整合： P01项目之间的整合以及与数据和结果的整合 如果是P01的话。第一级整合将基于黑色素瘤的假设 进展是由单个或几个生物功能的调节驱动的， 功能可以通过不同的机制进行修饰：种系和体细胞突变， 通过遗传和体细胞多态性，甲基化， 和环境暴露。我们期望在结果之间找到更强的重叠 是由不同的项目在生物功能水平上产生的，而不是在基因水平上。 黑色素瘤一直是研究的热点，有大量的数据和结果与黑色素瘤有关 进步已经产生。我们将联合收割机将P01产生的数据与TCGA结合， GEO、GTEx、ONCOMINE、人类蛋白质图谱和其他公共来源。使用的数据来自 外部资源将使我们能够测试和完善这一P01的关键发现。