Semantic analysis of behavior in a DNA-functionalized molecular swarm

TL;DR

This paper introduces semantic embedding techniques to analyze and interpret behaviors in DNA-functionalized molecular swarms, enhancing understanding and optimization of such nanoscale systems.

Contribution

It applies semantic embedding to molecular swarm simulations, enabling better explainability and control of complex behaviors in DNA-functionalized microtubule systems.

Findings

Semantic atoms match expected behaviors in simulations.

Decomposition accurately reflects external control impacts.

Enhances explainability of molecular swarm experiments.

Abstract

In this paper, we propose applying semantic embedding to learn the range of behaviors exhibited by molecular swarms, thereby providing a richer set of features to optimize such systems. Specifically, we consider a standard molecular swarm where the individuals are cytoskeletal filaments (called microtubules) propelled by surface-adhered kinesin motors, with the addition of DNA functionalization for further control. We extend a microtubule model with that additional interaction and show that the extracted semantic atoms from simulation results match the expected behaviors. Moreover, the decomposition of each frame in the simulations accurately describes the expected impact of the external control values. Those results provide relevant leads towards the explainability of simulated experiments, making them more reliable for designing and optimizing in-vitro systems.