Organisms respond to complex and dynamic external conditions through a series of interrelated behavioral, physiological, morphological, and molecular mechanisms. Advances in technology and deepening connections to multiple biological disciplines, including molecular, neuro-, and developmental biology, are revolutionizing the study of organisms in the wild. Biological data of unprecedented scale and complexity—from genomes to behaviors—now sit alongside detailed environmental records from satellite imagery and global weather networks, offering an unparalleled opportunity to understand and predict organismal resilience by linking genotype to phenotype to environment. Yet the analytical tools needed to connect and analyze such disparate datasets have lagged behind. New advances in artificial intelligence (AI) and machine learning (ML) are poised to change that, and in doing so, to greatly expand our understanding of the natural world. By merging organismal biology with computer science to build the field of computational organismal biology, NSCORE will develop the AI tools and expertise needed to synthesize data—from molecules to individuals to ecosystems—and predict how organisms remain resilient in the face of change.
This project is supported by the U.S. National Science Foundation under Cooperative Agreement 2438843. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.