Advanced Proteome Informatics of Cancer

 描述(由申请人提供)：这是我们在密歇根大学的T32癌症高级蛋白质组信息学培训计划(PICTP)的续签申请。国家癌症研究所在癌症蛋白质组学的新技术平台上进行了大量投资，最近通过临床蛋白质肿瘤分析联盟(CPTAC)进行了投资。蛋白质组对于了解癌症的功能基因组学和系统生物学，以及发现和验证治疗和预防的生物标记物候选和分子靶点至关重要。复杂的蛋白质组分析需要先进的信息学来处理样本的复杂性、蛋白质浓度的极端动态范围、翻译后修饰、替代剪接异构体、对各种扰动的反应以及数据库和数据格式的差异。此外，对使用多种组学技术(蛋白质组学、基因组学、代谢组学等)产生的数据进行综合分析。已经成为重建癌症靶向通路的一种有效方法。PICTP的主要目标是解决目前缺乏能够有效生成和生物信息学分析自己的蛋白质组数据的科学家，利用CPTAC和其他公开可用的大规模癌症蛋白质组数据集，并执行多级数据集成。PICTP是一个多学科的培训项目，也是非常独特的， 在密歇根大学和全国范围内。该中心位于大学范围内的计算医学和生物信息学中心(CCMB)，为来自不同背景的学生提供了在所有三个PICTP重点领域-癌症生物学、蛋白质组学和生物信息学-熟练掌握技能的机会。我们有一个由癌症研究人员、生物信息学家、统计学家、化学家和软件工程师组成的强大社区。我们的教师和学生领导着人类蛋白质组组织(HuPO)的倡议，开发和全球部署数据存储库和数据分析系统，并为蛋白质组信息学和组学数据集成创建新的算法。我们的学员来自密歇根大学较大的研究生项目(包括生物信息学、病理学、化学、生物医学工程和统计学)，并通过课程、研讨会和期刊俱乐部接受癌症生物学、生物信息学和蛋白质组学方面的培训。PICTP强烈鼓励每个受训人员由一名癌症研究人员和一名计算科学家进行双重指导。我们将进一步加强我们的培训计划，为我们的T32学员增加一个特别的年度工作坊，内容是关于HuPo人类蛋白质组项目的指标分析。总之，我们正在进行的癌症蛋白质组信息学NCI培训计划培养了新一代科学家，为跨学科生物医学研究的独立职业生涯做好了充分准备，加强了教师研究，并支持了NCI的目标。

 DESCRIPTION (provided by applicant): This is a renewal application for our T32 Advanced Proteome Informatics of Cancer Training Program (PICTP) at the University of Michigan. The National Cancer Institute has made substantial investments in new technology platforms for cancer proteomics, most recently through the Clinical Proteomic Tumor Analysis Consortium (CPTAC). The proteome is critical to understanding functional genomics and systems biology of cancers and to discovery and validation of biomarker candidates and molecular targets for therapy and prevention. Sophisticated analysis of proteomes requires advanced informatics to deal with the complexity of specimens, the extreme dynamic range of protein concentrations, post-­-translational modifications, alternative splice isoforms, responses to all sorts of perturbations, and differences in databases and data formats. Furthermore, integrative analysis of data generated using multiple omics technologies (proteomics, genomics, metabolomics, etc.) has emerged as a powerful approach for reconstructing targetable pathways in cancer. The main goal of PICTP is to address the current scarcity of scientists able to effectively generate and bioinformaticly analyze their own proteomics data, to take advantage of CPTAC and other publicly available large-scale cancer proteomics datasets, and to perform multilevel data integration. PICTP a truly is a multi- disciplinary Training Program that is also very unique, with the U of M and nationally. Anchored in the university-­-wide Center for Computational Medicine and Bioinformatics (CCMB), it provides an opportunity to students from diverse backgrounds to become well skilled in all three PICTP focus areas - cancer biology, proteomics, and bioinformatics. We have a robust community of cancer researchers, bioinformaticians, statisticians, chemists, and software engineers. Our faculty and students are in the leadership of Human Proteome Organization (HUPO) initiatives, development and global deployment of data repositories and data analysis systems, and creation of new algorithms for proteome informatics and omics data integration. Our trainees come from larger Graduate Programs within the U of M (including Bioinformatics, Pathology, Chemistry, Biomedical Engineering, and Statistics) and receive training in cancer biology, bioinformatics, and proteomics through courses, seminars, and the journal club. PICTP strongly encourages dual mentorship of each trainee by a cancer researcher and a computational scientist. We will further strengthen our Training Program with an addition of a special Annual Workshop for our T32 trainees on the Analysis of Metrics for the HUPO Human Proteome Project. In summary, our ongoing NCI training program in Proteome Informatics of Cancer trains a new generation of scientists well prepared for an independent career in interdisciplinary biomedical research, enhances faculty research, and supports NCI goals.