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October 19, 2025Open Access

STAGED: A Multi-Agent Neural Network for Learning Cellular Interaction Dynamics

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Authors

JRJaqueline RochaUniversidade de São PauloKXKe XuMinistry of Education of the People's Republic of ChinaXSXingzhi SunYale University

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Overview

Observed enhanced modeling of intercellular and intracellular interactions, suggesting improved understanding of cellular states.

Key Points

  • The approach enables a more adaptive and accurate representation of cellular dynamics, addressing limitations of existing methods.
  • Using graph ODE networks, the model dynamically learns interaction strengths, effectively capturing interaction dynamics.
  • The integration of agent-based modeling with deep learning provides a novel framework for studying complex cellular interactions.
  • Trained on simulated and inferred data, this method enhances clarity into how cells communicate and regulate gene expression.

Cite This Study

Rocha et al. (2025) studied this question.

synapsesocial.com/papers/68f4b10d3d9d770bbc696de8https://doi.org/10.48550/arxiv.2507.11660
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