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 过去十年，由于多模式癌症组学数​​据的发展，多模式癌症组学数​​据呈指数增长。 可捕获 DNA、RNA、蛋白质和代谢水平数据的高通量尖端技术。有一个 迫切需要培训下一代基因组学数据科学家，他们的任务是翻译基因组学 这些高维数据的复杂整合，利用复杂的统计数据提供精准的肿瘤学 以及计算方法和工具。由于行业的诱惑不断增加，存在着巨大的威胁 学术界的“人才流失”在数据科学和高维领域尤其普遍 计算能力。该提案旨在开发纪念斯隆凯特琳癌症中心的基因组学 硕士生研究经验 (GEMS) 奖学金计划，一个结构化的专业计划 针对生物统计学、统计学、数据科学、计算机科学或相关领域的硕士学位学员 定量训练（5年内每年夏天6次）。 GEMS 项目是一个为期 12 周的沉浸式实践项目 癌症基因组学的跨学科夏季研究经验，其中几个组成部分使 计划独特：获得世界领先的癌症基因组学数据和工具资源，定量和 科学的双指导模式，与同行顾问配对，以及前沿的讲座/迷你研讨会系列 由世界专家项目教师提供的基因组技术和高维数据分析。这 研究员将获得全基因组和全转录组下一代测序的经验 数据并真正了解高维数据分析、先进的统计基因组学概念 和建模技术、并行计算和可重复的研究范式。这个组合大 项目中的数据资源、计算基础设施、教学讲座和实践研讨会系列 教师创造了一个独特的环境，在其中追求以下目标：1）发展基因组学 研究实习计划，每年招收 6 名学生，为他们提供为期 12 周的沉浸式实践 解决前沿癌症基因组学研究问题的研究培训经验； 2）开发和 促进双向评估计划，为参与者及其他们的人员提供及时的评估和反馈 导师； 3) 跟踪参与者随时间的职业发展，以评估计划的成功并 支持项目校友追求基因组学领域的定量职业。 GEMS 将由纪念馆的 2 位 PD 共同领导 斯隆凯特琳癌症中心拥有长期有影响力的研究、指导和成功的记录 知识翻译。双团队指导方法将为学生做好跨学科的准备 转化科学劳动力并将学习成为批判性思考者。 GEMS 将为学员做好有影响力的准备 担任组学数据科学家，并将获得基因组学癌症医学方面的劳动力培训。