Finding Your Inner Modeler: Exploring Modern Paradigms in Biology Research

For many years, there have been efforts to bring quantitative theory and computational modeling—long cornerstones of engineering and the physical sciences—more firmly into the domain of molecular and cell biology. Harnessing computational modeling in its various forms has helped advance fundamental understanding of how molecular interactions contribute to cellular function, along with accelerating biotechnological innovation. However, the research landscape is changing faster than ever, due to advances in measurement technologies (e.g., sequencing, imaging) and computing (e.g., machine learning and artificial intelligence). This project seeks to provide a forum in which the community can discuss and define best practices for integrating experimental and computational biology research, given the rapid changes in the modern research landscape. The Broader Impacts of the work include the intrinsic merit of the proposed work as it will help the broad community cell and molecular biologists keep pace with new advances in computation and bring computational scientists into the field of biology. The work will also involve the training of a breadth of young scientists. An overarching goal of this project is to connect and strengthen the interdisciplinary research community that is harnessing computational modeling in its various forms to tackle complex biological questions. The major activity will be an annual meeting, which will draw researchers from a broad cross section of disciplines, types of institutions, career stages, and geographic locations (primarily U.S.). Participants in this Research Coordination Network will tackle critical questions facing the field regarding methodology, training, collaboration, standardization, and more. Expected outcomes include the kickstarting of new collaborations, better understanding and documentation of the relevant stakeholders (e.g., industries, centers, institutions, programs), and dissemination of best practices and updated paradigms for experimental-computational biology research. 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.