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Volume 41 Issue 11, November 2023

Mathematical models of T cell regulation

Machine learning models for T cell dynamics: Kirouac et al. encode knowledge about T cell biology through mathematics and use computer simulations to explore the mechanisms underlying clinical observations and biomolecular data.

See Kirouac et al.

Image: Nicole Sims. Cover Design: Erin Dewalt.

Volume 41 Issue 11

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  • Leveraging advances in hardware and probes, we have combined innovations in optics and algorithms to allow automated single-molecule-based super-resolution imaging at unprecedented throughput. This approach allows us to obtain nanoscale information from large cell populations, bridging the gap between imaging and indirect ensemble methods.

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  • Sequencing individual cells in a sample enables scientists to infer the unique characteristics of important subsets. Single-cell sequencing methods that rely on microfluidics for cell barcoding are limited in speed, scale and flexibility. We developed a technique that uses particle-templated emulsification instead of microfluidics and can process millions of cells within minutes.

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