SIAM News Blog

“Understanding the Rules of Life”

An NSF Big Idea for the Mathematical Sciences

By Adriana Dawes, Marisa Eisenberg, and Padmanabhan Seshaiyer

In 2019, the National Science Foundation (NSF) is expected to have invested $30 million in “Understanding the Rules of Life,” one of the agency’s 10 Big Ideas. How can we identify and support emerging opportunities for the mathematical sciences community to contribute to this big idea and help serve the nation’s future?

To identify these opportunities, we received a grant from the NSF titled Collaborative Research: RoL: FELS: Workshop – Rules of Life in the Context of Future Mathematical Sciences (DMS1839608).

We gathered input from researchers in a variety of fields spanning mathematics and biology, and defined emerging research challenges and priorities in mathematical biology in response to “Understanding the Rules of Life.” Participants provided specific suggestions and feedback to the prompt, “What should the strategic priority areas of mathematical biology be under the NSF’s Rules of Life?” The six key topic areas that we identified are as follows:

  1. Understanding the Rules of Life in Integrative Biological Systems: Transients and Noise. The recommendation is to foster new solicitations or programs that focus on developing a broad dynamical theory for transients and quasi-stationary states in biological systems. This includes research examining the relationships between transients, noise, heterogeneity, and the distinct effects of experimental and biological variation, including the high risk/high reward of creating new theory and mathematical approaches to account for these disparities.

  2. The Mathematical Foundations of Data-Inspired Biology: Learning Rules of Life from Data. This topic seeks to develop programs or solicitations that support the necessary foundational and methodological work pertaining to model and data dimension reduction methods; rigorous estimation in network analysis; the linking of models with big data; and a unified theoretical framework for parameter estimation, parameter identifiability, and model selection. It also requires close collaboration between data collection and theory to ensure relevance and impact. Thus, a focus on programs that link theoretical predictions with data collection is strongly recommended for this priority area.

  3. Bridging Scales to Understand New Rules of Life. The suggestion here is to create programs that help develop an understanding of how the rules of life transition across scales; one can do so by building models and approaches that span spatial and temporal scales to uncover consistent biological principles. This theme encompasses multiscale phenomena, wherein dynamics at one scale directly affect those at other scales. It thus requires the collection of biological data across scales and the construction of unifying multiscale models.

  4. A New Fitness Landscape for Mathematical Theory: Quantifying Adaptation and Selection in Understanding Fundamental Rules of Life. Researchers recommended programs or solicitations that support further development of analytical techniques, including modeling trait tradeoffs, trait plasticity, and complex traits. They also proposed the incorporation of high-dimensional data, such as that from sequencing and gene expression. These programs would support efforts to address important open questions, including the following: What is the most appropriate way to define fitness? How do we reconstruct phylogenetic evolutionary histories of species with new data? How do we understand community genomics and eco-evolutionary dynamics across species and timescales? These questions can help build the genotype-to-phenotype map and generate insight into the fundamental rules of life.

  5. Mathematics for the Anthropocene Era: Rules of Life in the Context of Human Impact on Natural Systems. Obtaining a thorough understanding of human impact and developing forecasting, prediction, and control methods will require a range of analytical approaches (e.g., dynamical systems, optimization, game/decision theory, etc.) and data (satellite, sensors, social media, cell phone data, etc.). Programs that integrate or develop mathematical and data-based methods for understanding interactions between humans and natural systems are thus desirable. Also recommended was the expansion and development of interdisciplinary programs or solicitations that meaningfully draw from the range of disciplines involved in the interactions of human and natural systems. These interactions span both mathematics and biology, as well as adjacent fields like behavioral and social sciences, economics, health sciences, and environmental sciences.

  6. Broader Impacts: Convergence of Research and Education for the Rules of Life. Another recommendation included the creation of programs to enhance student training and research at the intersection of biological and mathematical sciences. These programs will help broaden student experiences and prepare them for undergraduate, graduate, and post-graduate study, in addition to careers at the interface of mathematics and biology. Evaluation and impact assessment of these programs will lead to increased workforce effectiveness and improved understanding of the rules of life. Programs for faculty development—including long-term training grants, conferences, and workshops to connect scientists, mathematicians, and educational researchers—will enable innovative, cross-disciplinary solutions to grand challenge problems at the junction of mathematical and biological sciences.

Ami E. Radunskaya of Pomona College (left) and Marisa Eisenberg of the University of Michigan (right) present ideas, suggestions, and feedback on strategic priority areas of mathematical biology at the “Rules of Life in the Context of Future Mathematical Sciences” workshop. Photos courtesy of Padmanabhan Seshaiyer.

All six priority areas identified several common themes in terms of recruitment, training, and retention. In particular, participant input reinforced the importance of interdisciplinary instruction to provide integrated depth in mathematics and biology. Multiple groups noted statistical training and working with data as key elements of this preparation. They also emphasized the need for programs at all levels (student and faculty), and remarked that diverse perspectives are important for deeply interdisciplinary research. All participants agreed that developing integrated programs that blend mathematics, statistics, and biology is particularly critical for success in every topic area.

The intellectual impact of supporting research in these emerging priority areas is clear. Advances at the interface of mathematics and life sciences urgently need rigorous and comprehensive quantitative methods. In addition to furthering our understanding of the rules of life, these efforts will grow convergent research and make the most of the data revolution.

These ideas were gathered at a workshop that brought together a highly diverse group of individuals in mathematical biology in November 2018.

Adriana Dawes is an associate professor in the Departments of Mathematics and Molecular Genetics at The Ohio State University. She is also an associate director at the Mathematical Biosciences Institute and a member of the Society for Mathematical Biology’s mentoring committee. Marisa Eisenberg is an associate professor in the Departments of Epidemiology, Complex Systems, and Mathematics at the University of Michigan. She is also co-chair of the Doctoral Program in Epidemiologic Science. Padmanabhan Seshaiyer is a professor of mathematical sciences and the Associate Dean for Academic Affairs in the College of Science at George Mason University. He currently serves as chair of the SIAM Diversity Advisory Committee, and was formerly a program director in the Division of Mathematical Sciences at the National Science Foundation.

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