MRI: Acquisition of a Computer Server for Research, Research Training and Education in the STEM Departments at Indiana University South Bend

该项目购买一台专用服务器作为增强数据存储空间访问的交钥匙解决方案，旨在促进学生参与使用大型数据集的科学、技术、工程和数学(STEM)领域的研究项目。IUSB的生物、信息学、物理和数学系将利用这一仪器，在一个教授承担大量教学负担的机构中，主要为本科生服务。许多研究项目涉及计算机密集型任务，例如，基因组分析和Hi-C数据。HI-C是3C(染色体确认捕获)的扩展，能够以一种公正的、全基因组的方式识别远程相互作用。该机构已经开设了数据挖掘、生物信息学和基因组学课程，向来自不同学科的学生传授分析大数据所需的技能，这反过来又需要使用服务器来执行计算密集型任务。因此，这台服务器增强了校园的计算结构，使跨多学科的研究能够更好地理解复杂情况下的决策。布罗德影响：此次收购为机构内的研究和教育提供了有用的技术能力。该服务器将：-用于教授数据挖掘、基因组学和生物信息学等数据密集型课程；-显著改善培训学生处理大数据的机会；以及-使本科生参与的研究项目能够在会议和科学会议上展示。这些数据密集型课程将由生物、生物化学、计算机科学、信息学的本科生以及应用数学和计算机科学专业的研究生学习。该仪器将是共享的，而不是重复的，这将鼓励实地交叉，这至少可能使知识交叉，甚至开辟新的研究途径。

This project, acquiring a single dedicated server as a turnkey solution for enhancing access to data storage spaces, aims to promote student participation in research projects in Science, Technology, Engineering and Math (STEM) areas that use large data sets. The departments of biology, informatics, physics, and mathematics at IUSB will take advantage of the instrument in an institution where professors with substantial teaching loads serve mainly undergraduate students. Many of the research programs involve compute intensive tasks, for example, analysis of genomes and Hi-C Data. Hi-C, an extension of 3C (chromosome confirmation capture) is capable of identifying long range interactions in an unbiased, genome-wide fashion. Data mining, bioinformatics, and genomics courses already in place at the institution teach students from different disciplines the skills needed for analysis of big data, which in turn require the use of a server to carry on the compute intensive tasks. Hence, this server enhances the computational structure of the campus and enables research studies across multiple disciplines to gain a better understanding of decision making under complex situations.Broader Impacts:This acquisition provides a useful technology capability for research and education within the institution. The server will:- Be used to teach data intensive courses like data mining, genomics, and bioinformatics;- Significantly improve the opportunities for training students in handling big data; and- Enable research projects involving undergraduates to be presented in conferences and scientific meetings.The data intensive courses will be taken by undergraduates from biology, biochemistry, computer science, informatics, and graduate students from applied mathematics and computer science programs. The instrument will be shared rather than duplicated, encouraging field-crossing that might at least enable knowledge crossing or even open new research avenues.