NRT-DESE: Generating, Analyzing, and Understanding Sensory and Sequencing Information--A Trans-Disciplinary Graduate Training Program in Biosensing and Computational Biology

生物传感使用先进的半导体技术和基于下一代DNA测序的方法，以前所未有的规模产生关于生物系统的信息。这项国家科学基金会研究培训(NRT)奖为科罗拉多州立大学的硕士和博士生准备了从大量传感器和基因组数据中提取意义的工具。通过创新的课程和实习，学员将学会处理生物学家、计算机科学家和工程师无法单独克服的新的计算、统计、数学和工程挑战。这一培训计划有助于培养新一代科学家和工程师，他们能够解决与各种学科中的大数据集有关的复杂问题。此外，该计划建立了一个由大学、K-12学校、社区学院和行业组成的社区，以便更广泛地参与有效的科学发现、教学和学习。与培训计划相结合的研究活动将涉及对增进对生物科学面临的一些基本数据相关问题的理解至关重要的主题。跨学科团队将处理涉及生物传感器、微生物检测、基因表达调控以及进化基因组学和基因组组装的研究。工程、生命科学、计算机科学、数学和统计学的教职员工将开发灵活、可定制的培训模块集合，为每个学生创建个性化的培训体验，而不考虑他们的背景。学员将开发处理、分析、可视化和理解来自生物传感和下一代DNA测序的大数据集的技能和工具。此外，该计划纳入了广泛的可转移技能培训，使受训人员能够在学术界内外从事和领导以数据为中心的研究。

Biosensing using advanced semiconductor technologies and methods based on next generation DNA sequencing generate information about biological systems at an unprecedented scale. This National Science Foundation Research Traineeship (NRT) award prepares master's and doctoral students at Colorado State University with the tools to extract meaning from huge amounts of sensor and genomics data. Through innovative curricula and internships, trainees will learn to handle the new computational, statistical, mathematical, and engineering challenges that biologists, computer scientists, and engineers are unable to overcome alone. This traineeship program contributes to a new generation of scientists and engineers who are able to tackle complex problems related to large datasets in a variety of disciplines. Moreover, this program builds a community of university, K-12 schools, community colleges, and industry for a wider participation of effective scientific discovery, teaching, and learning.Research activities integrated with the training program will address themes critical to advance understanding of some fundamental data-related questions facing biological sciences. Interdisciplinary teams will tackle research involving biological sensors, detection of microbes, regulation of gene expression, and evolutionary genomics and genome assembly. Faculty across engineering, life sciences, computer science, mathematics, and statistics will develop a flexible, customizable collection of training modules, to create a training experience personalized for each student regardless of their background. Trainees will develop the skills and tools to process, analyze, visualize, and understand large datasets from biosensing and next generation DNA sequencing. Additionally, the program incorporates a wide range of transferrable skills training so that trainees will be well equipped to engage and lead data-centric research within or outside academia.