TI²PS：面向随机多细胞模式形成的拓扑感知逆向设计框架
TI$^2$PS: A Topology-Informed Inverse Design Framework for Stochastic Multicellular Pattern Formation
- NTT, Inc.（NTT公司）
- Georgia Institute of Technology（佐治亚理工学院）
机构由 AI 辅助整理，请以论文原文为准。
中文总结 AI 辅助
本研究提出TI²PS框架，整合贝蒂向量与逆向代理建模，以斑马鱼色素模式为验证对象，仅用10%训练数据即优于全数据训练的PointNet++，实现多细胞ABBM参数的高效准确估计。
中文摘要 AI 辅助
本研究提出了一种新框架，用于基于基于智能体的模型（agent-based model, ABM）估计参数，以重现目标多细胞模式。多细胞ABBM面临两大主要挑战：一是估计细胞级参数（智能体特定变量），二是在细胞随机增殖与死亡条件下定量评估多细胞排列的拓扑特征。为应对这些挑战，本研究整合了两种方法：贝蒂向量（Betti vectors）与逆向代理建模。通过拓扑数据分析得到的贝蒂向量可一致表征多种多细胞空间构型的特征；逆向代理建模则能从目标模式直接推断对应的ABBM参数。本研究以斑马鱼色素模式形成为例验证了所提框架，该模式是多细胞相互作用驱动模式形成的代表性模型。结果表明，所提框架成功估计了ABBM参数，且在所有评估指标上，仅使用10%训练数据的本方法表现优于使用100%数据的传统方法PointNet++。
英文摘要
This study proposes a novel framework to estimate parameters for reproducing target multicellular patterns using an agent-based model (ABM). Two major challenges in multicellular ABMs are estimating cell-level parameters (agent-specific variables) and quantitatively evaluating the topological characteristics of multicellular arrangements under stochastic cell proliferation and death. To address these challenges, we integrate two approaches: Betti vectors and inverse surrogate modeling. The Betti vectors obtained through topological data analysis can consistently represent features of a wide range of multicellular spatial configurations. The inverse surrogate modeling enables direct inference of the corresponding ABM parameters from the target patterns. We validated the proposed framework using zebrafish pigment pattern formation, a representative model of pattern formation driven by multicellular interactions. The results demonstrate that our framework successfully estimates ABM parameters and outperforms conventional methods such as PointNet++. Notably, the proposed method, which used only 10% of the training data, outperformed PointNet++, which used 100% of the data, across all evaluation metrics.
