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Abstract Quantifying the inheritance of regulatory networks among proteins during asymmetric cell division remains a challenge due to the complexity of these systems and the lack of robust mathematical definitions for inheritance. We propose a novel statistical framework called ODEinherit to measure how much a mother cell’s regulatory network explains its daughter’s trajectories, addressing this gap. Using time-lapse microscopy, we tracked the expression dynamics of six proteins across 85 dividingS. cerevisiaecells, observed over eight hours at 12-minute intervals. Our framework employs a two-step approach. First, we estimate an ordinary differential equation (ODE) system for each cell to characterize protein interactions, introducing novel adjustments for non-oscillatory time series and leveraging multi-cell data. Second, we assess inheritance by clustering cells based on cycling markers and quantifying how well a mother’s regulatory network predicts her daughter’s. Preliminary findings suggest stage-dependent differences in inheritance rates, paving the way for applications in cellular stress response and cell-fate prediction studies across generations. 

Abstract Although single-cell and spatial sequencing methods enable simultaneous measurement of more than one biological modality, no technology can capture all modalities within the same cell. For current data integration methods, the feasibility of cross-modal integration relies on the existence of highly correlated, a priori ‘linked’ features. We describe matching X-modality via fuzzy smoothed embedding (MaxFuse), a cross-modal data integration method that, through iterative coembedding, data smoothing and cell matching, uses all information in each modality to obtain high-quality integration even when features are weakly linked. MaxFuse is modality-agnostic and demonstrates high robustness and accuracy in the weak linkage scenario, achieving 20~70% relative improvement over existing methods under key evaluation metrics on benchmarking datasets. A prototypical example of weak linkage is the integration of spatial proteomic data with single-cell sequencing data. On two example analyses of this type, MaxFuse enabled the spatial consolidation of proteomic, transcriptomic and epigenomic information at single-cell resolution on the same tissue section.