用语义嵌入分析DNA功能化分子集群行为，提升系统可解释性。
Semantic analysis of behavior in a DNA-functionalized molecular swarm
- 通过语义嵌入学习微管集群的行为模式
- 模拟结果中提取的语义原子匹配预期行为
- 适合研究生物分子系统设计与优化的科研人员
本文提出将语义嵌入应用于分子集群行为分析，以学习其展现的行为范围，从而为优化此类系统提供更丰富的特征。我们研究了由表面附着的驱动蛋白马达推动的微管（cytoskeletal filaments）组成的典型分子集群，并引入DNA功能化实现进一步调控。扩展了微管模型以包含该相互作用，结果显示从模拟结果中提取的语义原子与预期行为一致。此外，模拟每一帧的分解准确反映了外部控制值的影响。这些结果为模拟实验的可解释性提供了有效线索，使其在体外系统设计与优化中更具可靠性。
原文摘要 · Abstract (English)
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.
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