Semantic analysis of behavior in a DNA-functionalized molecular swarm

2026-04-06

AI Summary

This work addresses the challenge of interpreting the complex, externally controlled behaviors of DNA-functionalized microtubule ensembles by introducing semantic embedding methods into molecular collective behavior analysis for the first time. By integrating microtubule dynamics modeling, DNA-mediated interaction simulations, and behavioral feature decomposition, the approach extracts interpretable “semantic atoms” from simulation data that effectively capture the system’s dynamic response to external control parameters. Experimental results demonstrate that the extracted semantic atoms align closely with expected behavioral patterns, significantly enhancing the predictability and reliability of in vitro molecular system design.

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.

Problem

• molecular swarm
• semantic analysis
• DNA functionalization
• microtubules
• behavior representation

Innovation

• semantic embedding
• molecular swarm
• DNA functionalization
• microtubule dynamics
• explainable simulation