Statistical mechanics meets single-cell biology

Single-cell omics is transforming our understanding of cell biology and disease, yet the systems-level analysis and interpretation of single-cell data faces many challenges. In this Perspective, we describe the impact that fundamental concepts from statistical mechanics, notably entropy, stochastic processes and critical phenomena, are having on single-cell data analysis. We further advocate the need for more bottom-up modelling of single-cell data and to embrace a statistical mechanics analysis paradigm to help attain a deeper understanding of single-cell systems biology. In this Perspective, Teschendorff and Feinberg describe how single-cell analysis methods based on statistical mechanics can provide valuable insights into developmental phenomena, such as differentiation potency and lineage trajectories, as well as disruption of these processes in cancer.

Automated summary

Single-cell omics is revolutionizing our understanding of cell biology and disease, but the analysis and interpretation of single-cell data face challenges. Concepts from statistical mechanics, including entropy, stochastic processes, and critical phenomena, are impacting single-cell data analysis. Embracing bottom-up modeling and a statistical mechanics analysis paradigm can enhance our understanding of single-cell systems biology. Teschendorff and Feinberg highlight how statistical mechanics-based single-cell analysis methods offer insights into developmental phenomena and cancer processes.