REU Site: Interdisciplinary Undergraduate Research in Discrete Mathematical and Computational Biology

雷曼学院关于离散数学和计算生物学跨学科本科生研究的REU计划是为大学早期的本科生提供的学年研究经验。该项目将在纽约城市大学雷曼学院运行，这是一家位于纽约布朗克斯区的指定少数族裔服务和拉美裔服务机构。学生将来自大纽约大都市区，那里有1890万人口和100多万大学生。至少一半的学生参与者将从科学、技术、工程和数学(STEM)研究机会有限的学术机构招聘，包括两年制大学。大量学生进入大学时计划学习理科，但毕业时却拿到了其他领域的学位。造成这一现象的因素很多，包括理科专业的课业负担较大，以及非理科专业成绩膨胀的拉动。在本科早期参与科学研究被认为是增加留存的一种方式，特别是对于在科学界历史上代表性不足的群体。我们的目标是在学生大学生涯的早期--在关键的转折点，许多人选择非科学专业--并提供一个支持性的环境，让他们在具有挑战性的、开放的研究问题上取得进展。传统上，REU项目侧重于高年级学生在大学最后一年前的暑假，而我们的项目将在他们大学生涯的早期阶段招收10名学生，并在学年期间运行。该项目的目标是让学生尽早参与一个动态的研究项目，展示研究如何融入他们的生活，并鼓励学生追求未来的研究机会。该计划旨在补充当地社区和四年制大学的学术时间表，在秋季学期的周五举行全天的现场会议，并在1月份的间歇期进行密集的计划。这个本科生研究项目的知识重点是一种简单但极其强大的模型：一棵“树”或非循环图。数学树结构在生物学和计算机科学中普遍存在，应用于从进化生物学到计算机科学等不同领域。结构的简单性产生了许多生物、计算和数学交叉领域的开放问题，这些问题对于优秀的学生来说是可以接近的。该计划旨在培养学生在研究和解决问题活动中的能力和独立性。学生群体将主要由二年级学生组成：许多人在从事公开研究项目、与他人合作和交流科学思想方面几乎没有经验。因此，该项目不假定过去的经验(除了在早期STEM课程中的成功，强调解决问题的技能)，并建立一个框架，推动学生走向独立。该课程结构提供了技术技能(如乳胶的使用、技术写作和海报设计)和学术主题(这将为应对开放的研究挑战提供额外的工具)和鼓励发展人际技能(如负责任的研究进行、大学互动和成功的协作技能)的框架。

The Lehman College REU program on interdisciplinary undergraduate research in discrete mathematical and computational biology is an academic year research experience for undergraduate students early in their college experiences. The program will be run at Lehman College of the City University of New York, a designated Minority Serving and Hispanic Serving Institution located in the Bronx, New York. Students will be drawn from the greater New York metropolitan area, which has a population of 18.9 million and has over a million college students. At least half of the student participants will be recruited from academic institutions where research opportunities in science, technology, engineering, and mathematics (STEM) are limited, including two-year colleges. Large numbers of students enter college planning to study science but exit with degrees in other fields. Many factors have been cited for the attrition, including the larger workloads for science majors and the pull of grade inflation of the non-sciences. Involvement in scientific research early in the undergraduate experience has been suggested as a way to increase retention, especially for groups historically underrepresented in the sciences. We aim to reach students early in their college career -- at a critical transition point where many choose non-scientific majors -- and provide a supportive environment to make progress on challenging, open research problems. While traditionally REU programs have focused on upper division students the summer before their final year of college, our program will recruit ten students at earlier stages in their college career and run during the academic year. The goals of this program are to involve students early in a dynamic research program, show how research can be integrated into their lives, and encourage the students to pursue future research opportunities. The program is designed to complement the academic schedules of the local community and four-year colleges with all-day on-site meetings on Fridays during the fall semester and an intensive program during the January intersession. The intellectual focus of this undergraduate research program is on a simple, but extremely powerful, model: a "tree" or acyclic graph. Mathematical tree structures are ubiquitous in biology and computer science, used in such diverse fields as evolutionary biology to computer science. The simplicity of the structure yields many open problems at the intersection of biology, computing, and mathematics that are approachable by strong students. The program is structured to build students' competence and independence in research and problem solving activities. The cohort of students will consist mostly of second year students: many will have little experience of working on open research projects, collaborating with others, and communicating scientific ideas. As such, the program assumes no past experience (other than success in early STEM courses that emphasize problem solving skills) and builds a framework that moves students towards independence. The program structure offers a mix of instruction in technical skills (such as the use of LaTeX, technical writing, and poster design) and academic topics (that will provide additional tools for tackling the open research challenges) as well as a framework to encourage the development of interpersonal skills (such as the responsible conduct of research, collegial interactions, and successful collaborative skills).