Title: Simplicial Biology

Abstract: In my thesis, I used physical principles to study conserved biology across scales, from gene expression within a single cell type up to the emergent behavior of networks of hundreds of millions of cells. I first showed that phenotypic variation within most human cell types is consistent with the bounds predicted by Pareto optimality, which enabled principled identification of cell function from transcriptomic data. Doing so required new software infrastructure, which I then developed and used to extend the findings across the tree of life, revealing that cell functions within a given cell type are conserved over vast evolutionary distances. I next turned to the octopus, a model organism for parallel and convergent evolution, to identify the cellular mechanisms it uses to sense and react to its environment, and how a complex sensory organ—the box camera eye—evolved repeatedly in divergent lineages. Finally, I zoomed out from molecules to emergent system-level behavior, using quantitative cuttlefish camouflaging trajectories to infer the behavior of neuronal networks in a biological brain, finding that their transition paths minimize transition energy in high dimensional space, and compare it qualitatively to mammalian brains to identify conserved behavior of the motor cortex.

Please contact Sofia Rakicevic-More for the Zoom link.