Advanced Proteome Informatics of Cancer

 描述（由申请人提供）：这是我们的T32高级蛋白质组信息学癌症培训计划（PICTP）在密歇根大学的更新申请。美国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组肿瘤分析联盟（CPTAC）进行了投资。蛋白质组对于理解癌症的功能基因组学和系统生物学以及发现和验证用于治疗和预防的生物标志物候选物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标本的复杂性、蛋白质浓度的极端动态范围、翻译后修饰、选择性剪接异构体、对各种扰动的响应以及数据库和数据格式的差异。此外，使用多种组学技术（蛋白质组学、基因组学、代谢组学等）生成的数据的综合分析也是一种新的技术。已经成为重建癌症靶向通路的有力方法。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学数据的科学家的问题，利用CPTAC和其他公开可用的大规模癌症蛋白质组学数据集，并进行多级数据集成。PICTP是一个真正的多学科培训计划，也是非常独特的， 与M和全国的U。它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一个机会，使他们能够熟练掌握所有三个PICTP重点领域-癌症生物学，蛋白质组学和生物信息学。我们有一个强大的癌症研究人员，生物信息学家，统计学家，化学家和软件工程师社区。我们的教师和学生是在人类蛋白质组组织（HUPO）倡议，开发和数据存储库和数据分析系统的全球部署，并为蛋白质组信息学和组学数据集成创建新的算法的领导。我们的学员来自M大学（包括生物信息学，病理学，化学，生物医学工程和统计学）内的大型研究生课程，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的培训。PICTP强烈鼓励癌症研究人员和计算科学家对每位学员进行双重指导。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研讨会，内容是HUPO人类蛋白质组项目的蛋白质分析。总之，我们正在进行的NCI癌症蛋白质组信息学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做好了充分准备，增强了教师的研究，并支持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.