Genomics Research Experience for Master's Students (GEMS) Fellowship

硕士生基因组学研究经验（GEMS）奖学金

• 批准号: 10628537
• 负责人: KATHERINE S PANAGEAS
• 金额: $ 11.39万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10628537
• 关键词: Academia; Address; Biomedical Research; Biometry; Brain Drains; Cells; Clinical; Clonal Evolution; Complex; Computing Methodologies; DNA; Data; Data Analyses; Data Science; Data Scientist; Decision Making; Degree program; Development; Discipline; Education; Educational workshop; Enrollment; Environment; Epidemiology; Evaluation; Exposure to; Faculty; Feedback; Fellowship; Fellowship Program; Genomic approach; Genomics; Goals; Individual; Industry; Internships; Interview; Learning; Letters; Malignant Neoplasms; Master of Science; Medicine; Memorial Sloan-Kettering Cancer Center; Mentors; Mentorship; Methodology; Methods; Modeling; Modernization; Participant; Patients; Performance; Population; Process; Program Evaluation; Proteins; RNA; Recommendation; Records; Reproducibility; Research; Research Project Grants; Research Training; Science; Scientist; Series; Statistical Methods; Structure; Students; Surveys; Techniques; Technology; Time; Training; Translating; Translational Research; Tumor Biology; biomarker discovery; cancer genomics; career; career development; computer infrastructure; computer science; data resource; disease classification; experience; follow-up; frontier; genomic data; genomic tools; hands on research; high dimensionality; knowledge translation; lectures; multidimensional data; multidisciplinary; multimodality; neoplasm resource; next generation; next generation sequencing; parallel computer; peer; precision oncology; programs; prospective; recruit; risk stratification; skills; statistics; student training; success; summer internship; summer research; theories; tool; transcriptome; whole genome

ABSTRACT The last decade has seen an exponential increase in multimodal cancer -omics data due to the development of high throughput cutting-edge technologies that capture DNA, RNA, protein and metabolite level data. There is a critical need for training the next generation of data scientists in genomics who can be tasked to translate the complex integration of these high dimensional data to deliver precision oncology using sophisticated statistical and computational methods and tools. Due to growing enticements from industry, there is significant threat of “brain drain” from academia that is especially prevalent among those with data science and high dimensional computational skills. This proposal seeks to develop the Memorial Sloan Kettering Cancer Center’s Genomics Research Experience for Master’s Students (GEMS) Fellowship Program, a structured and specialized program that targets master’s level trainees in biostatistics, statistics, data science, computer science or related quantitative discipline (6 per summer over 5 years). The GEMS program is a hands-on, 12-week immersive and interdisciplinary summer research experience in cancer genomics with several components that make the program unique: access to the world's leading resources of cancer genomics data and tools, a quantitative and scientific dual-mentoring model, pairing with a peer advisor, and a lecture/mini workshop series on cutting-edge genomic technologies and high dimensional data analysis given by program faculty who are world experts. The fellows will gain experience working with whole-genome and whole-transcriptome next-generation sequencing data and obtain a real understanding of high-dimensional data analysis, advanced statistical genomics concepts and modeling techniques, parallel computing and reproducible research paradigms. This combination of large data resources, computational infrastructure, didactic lecture and hands-on workshop series from program faculty creates a unique environment in which the following aims will be pursued: 1) develop a genomics research internship program that annually recruits 6 students to provide them a 12-week immersive hands-on research training experience addressing cutting edge cancer genomics research questions; 2) develop and facilitate a bi-directional evaluation plan to provide timely assessment and feedback for the participants and their mentors; and 3) track participants' career development over time to evaluate the success of the program and to support program alumni to pursue quantitative careers in genomics. GEMS will be co-led by 2 PDs at Memorial Sloan Kettering Cancer Center with long track records of impactful research, mentorship, and successful knowledge translation. The dual team mentoring approach will prepare students for the inter-disciplinary translational science workforce and will learn to become critical thinkers. GEMS will prepare trainees for impactful careers as -omics data scientists and will obtain work-force training in genomics cancer medicine.

抽象的 在过去的十年中，由于发展的多模式癌 - 组数据的指数增加 捕获DNA，RNA，蛋白质和代谢物水平数据的高吞吐量尖端技术。有一个 培训下一代数据科学家在基因组学上的批判性需要，他们可以被任务翻译 这些高维数据的复杂整合以使用复杂的统计数据提供精度肿瘤学 以及计算方法和工具。由于行业的诱因不断增长，因此存在重大威胁 学术界的“脑力流失”尤其普遍于数据科学和高维度 计算技能。该提案旨在开发纪念斯隆·克特林癌症中心的基因组学 硕士学生（GEMS）奖学金计划的研究经验，这是一个结构化和专业的计划 该目标针对大师级的生物统计学，统计学，数据科学，计算机科学或相关的学员 定量学科（在5年内每个夏季6个）。宝石计划是一个手工，12周的身临其境， 跨学科的夏季研究经验在癌症基因组学方面，有几个组成部分使得 独特的程序：访问癌症基因组学数据和工具的世界领先资源，一种定量和 科学的双重入学模型，与同伴顾问配对，以及有关尖端的演讲/迷你研讨会系列 基因组技术和高维数据分析由世界专家提供的计划教师提供。 研究员将获得与全基因组和全转录组的下一代测序的经验 数据并获得对高维数据分析，高级统计基因组学概念的真正理解 以及建模技术，并行计算和可再现的研究范例。大型结合 来自计划的数据资源，计算基础架构，教学演讲和动手讲习班系列 教师创造了一个独特的环境，其中将追求以下目标：1）开发基因组学 研究实习计划每年招募6名学生，为他们提供12周的身临其实的动手 研究培训经验解决尖端癌症基因组学研究问题； 2）发展和 促进双向评估计划，为参与者及其提供及时的评估和反馈 导师； 3）跟踪参与者的职业发展，以评估该计划的成功和 支持计划校友以购买基因组学的定量职业。宝石将由纪念馆的2 pds共同领导 斯隆·凯特林（Sloan Kettering）癌症中心具有长期有影响力的研究，精神训练和成功的记录 知识翻译。双重团队心理方法将使学生为跨学科的学生做好准备 转化科学劳动力，并将学会成为批判性思想家。宝石将为受训者做好有影响力的准备 职业作为 - 摩西数据科学家，并将获得基因组癌症医学的工作力量培训。