Ambitions for theory in the physics of life
arXiv:2401.15538 · doi:10.21468/SciPostPhysLectNotes.84
Abstract
Theoretical physicists have been fascinated by the phenomena of life for more than a century. As we engage with more realistic descriptions of living systems, however, things get complicated. After reviewing different reactions to this complexity, I explore the optimization of information flow as a potentially general theoretical principle. The primary example is a genetic network guiding development of the fly embryo, but each idea also is illustrated by examples from neural systems. In each case, optimization makes detailed, largely parameter-free predictions that connect quantitatively with experiment
Lectures at the 2023 Les Houches Summer School, Theoretical Biophysics. Revisions include some replacement figures with permissions, small clarifications in the text
References in corpus (10)
- A Tutorial on Principal Component Analysis
- Scaling Laws for Neural Language Models
- Active matter
- Genealogies of rapidly adapting populations
- The Principles of Deep Learning Theory
- Neural signal propagation atlas of C. elegans
- Features and dimensions: Motion estimation in fly vision
- Finding the last bits of positional information
- Transcription-dependent spatial organization of a gene locus
- Deriving a genetic regulatory network from an optimization principle