Codes For Life - Artificial Intelligence and Sustainable Software for Biomolecular Interactions

点击翻译按钮获取中文摘要

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).The modern study of biology is increasingly digital. Ever-expanding databases of genome sequences, protein structures, electronic health records, and biometric data may hold the key for solving crucial problems in many domains, such as biomedicine, agriculture, ecology, and forensics. Gathering useful information from this data requires advanced computer science skills as well as a deep understanding of biology. This National Science Foundation Research Traineeship (NRT) award to Rutgers University-Camden will meet this national need by training Master’s and doctoral degree students in the fundamental biology and biophysics of DNA and proteins, artificial intelligence (AI) methods, and professional best practices for team software development. The traineeship follows a new model for students and faculty mentors that combines innovative training support with increased expectations. While the program is designed to make science graduate training of any discipline more efficient, effective, and accessible, the NRT is specifically designed to overcome the challenges in training students in new fields between traditional domains of expertise. The project anticipates training 30 M.S. and 25 Ph.D. students, with an additional 300 M.S. and Ph.D. students expected to participate in a subset of the activities. Trainees will graduate with a combination of skills that are highly in-demand across academic, government, and industrial workplaces.The research and training activities of this NRT award are particularly focused on using AI and sustainably developed software to overcome the widening communication gap between genomicists and proteomicists. This communication gap, worsened by diverging scientific dialects, has prevented the synthesis of research advances and the development of new unifying biological principles. AI is a generalizable approach that is being increasingly used by both fields. Software is a powerful method for communication and bridging disciplinary divides. However, it must be accessible to both disciplines and developed to a standard that academic software rarely meets. The team proposes a new model for graduate training that combines evidenced-based methods, redesigned for improved sustainability, and original activities that satisfy an identified need. Training activities will include revised curricula, the introduction of efficient “just-in-time” short format high-quality training, an industry mentorship program integrated with the trainee’s research, and peer mentoring for expanding perspectives and sharing strategies. The traineeship will introduce the new “Codes for Life” track into an interdisciplinary graduate degree program at Rutgers University-Camden. Many activities will be extended to all students enrolled in this broad graduate program. As a result, this will provide a unique opportunity to evaluate activities with a large graduate student body without historical departmental constraints. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.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.