Predoctoral Training in Bioinformatics and Computational Biology

生物信息学和计算生物学博士前培训

• 批准号: 10715126
• 负责人: GARY E. BENSON
• 金额: $ 31.83万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10715126
• 关键词: Bioinformatics; Computational Biology; Training; pre-doctoral

Project Summary/Abstract Biomedical research is evolving rapidly as new high-throughput technologies, producing massive quantities of data, open new frontiers in data-driven predictive capabilities, boosting the applicability of complex data analysis and machine learning algorithms in areas ranging from personalized medicine and drug discovery to structural biology and microbial ecology. Simultaneously, high standards for ethical production, use, and open access to data have become essential. This new application seeks support for the Predoctoral Training Program in Bioinformatics and Computational Biology at Boston University which will train young scientists to become leaders in this transformational era. Ten predoctoral training slots per year are requested to fund five trainees each in years one and two. The curriculum includes a strong foundation in biological domain knowledge, advanced methodologies in the quantitative sciences (computing, mathematics, and statistics), an emphasis on reproducibility habits, awareness of algorithmic and racial bias in research, and extensive opportunities for developing scientific communications skills. Program features include: 1) three lab rotations, including the Wet-Lab Experience, which introduces new trainees to high-throughput experimental methods, 2) the Challenge Project, for first-year team research on open-ended, data-intensive biological problems, with an emphasis on rigor and reproducibility, 3) Programming workshops for computational skills development, 4) Algorithmic Bias workshops for recognizing biases in data collection and use, 5) a research-in-progress Student Seminar, 6) the annual International Workshop in Bioinformatics and Systems Biology, undertaken jointly with partner programs in Japan and Germany, 7) the annual Student-Organized Symposium, 8) a teaching requirement, and 9) the annual Program Retreat. Thirty-six faculty mentors from 14 departments, each with a strong quantitative component to their research, offer a wide range of interdisciplinary expertise in experimental, mathematical and computational approaches. All use rigorous and reproducible methods in their research, take an active role in Program activities, are committed to active mentoring, and will have taken mentor training by the start of Program funding. Three co-PDs, who have worked together for over a decade, will provide leadership. Each brings training strengths and administrative experience. An Executive Committee, including five additional faculty will oversee the Program, with direct input from the trainees through a Student Advisory Council. The Program offers extensive career development activities, multipronged avenues for student engagement, and a multidimensional scheme for ongoing evaluation.

项目摘要/摘要 生物医学研究正在随着新的高通量技术的迅速发展，产生了大量 数据，开放数据驱动的预测能力的新边界，增强了复杂数据的适用性 分析和机器学习算法，从个性化医学和药物发现到 结构生物学和微生物生态学。同时，道德生产，使用和开放的高标准 访问数据已成为必不可少的。这个新应用程序寻求支持培训前培训 波士顿大学的生物信息学和计算生物学计划，该计划将培训年轻科学家 成为这个变革时代的领导者。要求每年十个托管训练老虎机资助五个 一年和两年中的学员分别。该课程包括生物领域的强大基础 知识，定量科学（计算，数学和统计学）中的高级方法论） 强调研究中的可重复性习惯，对算法和种族偏见的认识以及广泛的 发展科学沟通技巧的机会。程序功能包括：1）三个实验室旋转， 包括湿lab体验，将新学员引入高通量实验方法，2） 对于开放式，数据密集型生物学问题的一年级团队研究的挑战项目， 强调严格和可重复性，3）计算技能开发的编程研讨会，4） 算法偏见研讨会，用于识别数据收集和使用中的偏见，5）进行研究 学生研讨会，6）生物信息学和系统生物学的年度国际研讨会 与日本和德国的合作伙伴计划共同，7）年度学生组织研讨会，8）a 教学要求，以及9）年度课程务虚会。来自14个部门的36位教师导师， 每个人都有强大的定量组成部分，提供了广泛的跨学科专业知识 实验，数学和计算方法。所有人都在其中使用严格且可重复的方法 研究，在计划活动中发挥积极作用，致力于积极指导，并将接受 从计划资助开始时，导师培训。三个共同工作，他们共同工作了十多年， 将提供领导。每个都带来培训的长处和行政经验。高管 委员会，包括另外五个教师将监督该计划，并直接获得学员的意见 通过学生咨询委员会。该计划提供了广泛的职业发展活动， 用于学生参与的多收益途径，以及持续评估的多维计划。