REU Site: ICompBio - Engaging Undergraduates in Interdisciplinary Computing for Biological Research

该REU网站奖授予位于田纳西州查塔努加的田纳西大学查塔努加分校，将在2019年至2021年的夏季为10名学生提供为期10周的培训。该REU侧重于为STEM专业的大学二年级和三年级学生提供跨学科计算生物学（iCompBio）培训。学生申请包括申请表、成绩单、个人陈述、简历和两封推荐信。申请将由一组教师研究导师进行审查。学生将学习各种计算方法，并将其应用于解决生物学问题。每位学生将由一名计算机科学导师和一名生物导师共同指导。将提供为期一周的计算训练营，教授学生使用R的基本数据科学，以及使用Python的高级数据处理和深度学习方法。生物学研究方向包括衰老与长寿、生态网络、生物多样性、微生物途径进化、水生生态、环境可持续性、纳米颗粒肥料、田间生态学、植物标本馆数字化、蛋白质结构、细胞膜结构等。计算训练包括编码、建模、仿真、深度学习神经网络、计算机视觉、并行计算、统计学、数据可视化、移动App开发等。学生们还将接受道德和负责任的研究行为方面的培训。预计总共有30名学生，主要来自研究机会有限的学校，将接受iCompBio的培训。学生将学习如何进行可重复的计算研究，并将通过GitHub公开他们的编码项目。学生也将被鼓励在科学会议上展示他们的研究成果。由生物基础设施部资助的所有REU站点计划将使用一种通用的基于网络的评估工具SALG URSSA来确定培训计划的有效性。课程结束后，将对学生进行跟踪，以确定他们的职业道路。学生将被要求回复通过NSF报告系统自动发送的电子邮件。有关该计划的更多信息可访问http://utc.edu/icompbio或联系PI（洪琴博士hong-qin@utc.edu）或联合PI （Soubantika Palchoudhury博士soubantika-palchoudhury@utc.edu）。该奖项反映了美国国家科学基金会的法定使命，并通过基金会的智力价值和更广泛的影响审查标准进行了评估，认为值得支持。

This REU Site award to the University of Tennessee at Chattanooga, located in Chattanooga, TN, will support the training of 10 students for 10 weeks during the summers of 2019 to 2021. This REU focuses on interdisciplinary computational biology (iCompBio) training for college sophomores and juniors in STEM majors. The student application includes an application form, transcripts, a personal statement, a resume, and 2 letters of recommendations. Applications will be reviewed by a team of faculty research mentors. Students will learn various computational methods and apply them to address biological questions. Each student will be jointly mentored by a computer science mentor and a biology mentor. A one-week computing bootcamp will be provided to teach students essential data science using R, and advanced data processing and deep learning methods using Python. The biological research topics include aging and longevity, ecological networks, biodiversity, microbial pathway evolution, aquatic ecology, environment sustainability, nanoparticle fertilizers, field ecology, herbarium digitization, protein structures, and cell membrane structures. The computing training includes coding, modeling, simulation, deep learning neural networks, computer vision, parallel computing, statistics, data visualization, and mobile App development. Students will also go through training in ethics and responsible conduct for research. It is anticipated that a total of 30 students, primarily from schools with limited research opportunities, will be trained in iCompBio. Students will learn how to conduct reproducible computational research, and will make their coding projects publicly available through GitHub. Students will also be encouraged to present their research results in scientific meetings. A common web-based assessment tool, SALG URSSA, used by all REU Site programs funded by the Division of Biological Infrastructure will be used to determine the effectiveness of the training program. Students will be tracked after the program in order to determine their career paths. Students will be asked to respond to an automatic email sent via the NSF reporting system. More information about the program is available at http://utc.edu/icompbio or by contacting the PI (Dr. Hong Qin at hong-qin@utc.edu ) or the co-PI (Dr. Soubantika Palchoudhury at soubantika-palchoudhury@utc.edu).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.