Core 2: Biostatistics and Bioinformatics

核心2：生物统计学和生物信息学--摘要/摘要 德克萨斯大学安德森癌症中心研究肝细胞癌孢子的首要目标 (肝细胞癌)是通过阐明潜在分子来促进创新的翻译研究 机制，表征新的生物标记物和功能途径，并开发新的靶点 治疗。这是一项合作努力，将通过将实验室和 翻译研究。生物统计和生物信息学核心将服务于规划和 进行孢子的研究。基于在提供生物统计学和 翻译研究的计算支持，Core 2将是一个全面的、多边的资源，用于 设计临床和基础科学实验，执行统计分析，开发创新 统计方法，并发表从这个肝细胞癌孢子产生的研究结果。核心2将 为正在进行的临床试验和其他试验的设计和实施提供指导 孢子研究，包括孢子项目、发展和职业提升项目，以及 其他核心。CORE 2还将提供生物统计和生物信息学建模、模拟技术和数据 项目和其他核心实现其特定目标所需的分析。核心2将生成统计数据 所有项目的报告，将协助项目调查人员发布科学成果，并将开发创新 与转化型肝癌研究相关的统计和生物信息学方法，包括新的非监督研究 构建生物标记物标记的方法。

Core 2: Biostatistics and Bioinformatics - SUMMARY/ ABSTRACT The primary goal of the University of Texas MD Anderson Cancer Center SPORE in Hepatocellular Carcinoma (HCC) is to facilitate innovative translational research through the elucidation of underlying molecular mechanisms, characterizing novel biomarkers and functional pathways, and exploiting novel targets for treatment. This is a collaborative effort that will accomplish these aims by integrating laboratory and translational research. The Biostatistics and Bioinformatics Core will serve multiple needs for the planning and conduct of the SPORE's research. Based on a strong track record for providing biostatistical and computational support for translational research, Core 2 will be a comprehensive, multi-lateral resource for designing clinical and basic science experiments, performing statistical analyses, developing innovative statistical methodology, and publishing the research results generated from this HCC SPORE. Core 2 will provide guidance in the design and conduct of clinical trials and other experiments arising from the ongoing research of the SPORE, including SPORE projects, Developmental and Career Enhancement projects, and other cores. Core 2 will also provide biostatistical and bioinformatic modeling, simulation techniques and data analyses needed by the Projects and other Cores to achieve their Specific Aims. Core 2 will generate statistical reports for all projects, will assist project investigators to publish scientific results and will develop innovative statistical and bioinformatics methods pertinent to translational HCC studies including new unsupervised approaches to biomarker signature construction.