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Digitize your Biology! Modeling multicellular systems through interpretable cell behavior.

Jeanette A I Johnson1,2, Genevieve L Stein-O'Brien1,2,3, Max Booth1

  • 1Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University. Baltimore, MD USA.

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Summary
This summary is machine-generated.

We developed a cell behavior hypothesis grammar to translate natural language rules into mathematical models. This enables scalable systems biology modeling, bridging single-cell data to emergent multicellular behaviors for hypothesis generation.

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Cellular Dynamics

Background:

  • Cells are dynamic systems, and understanding their evolution requires mathematical modeling beyond current spatial multi-omics.
  • Integrating biological knowledge with multi-omics data is crucial for predicting cellular behavior.

Purpose of the Study:

  • To introduce a cell behavior hypothesis grammar for creating computable mathematical models from natural language statements.
  • To enable systematic integration of biological knowledge and multi-omics data for predictive modeling.
  • To facilitate virtual 'thought experiments' for hypothesis generation in multicellular systems.

Main Methods:

  • Development of a conceptual framework: a cell behavior hypothesis grammar.
  • Utilizing natural language statements (cell rules) to construct mathematical models.
  • Application of the grammar to tumor biology and immunotherapy examples.

Main Results:

  • Demonstration of a reference implementation for the cell behavior hypothesis grammar.
  • Successful application in generating testable hypotheses through virtual experiments.
  • Bridging the gap between single-cell characterization and emergent multicellular behavior.

Conclusions:

  • The cell behavior hypothesis grammar provides a scalable approach for mathematical modeling in systems biology.
  • It facilitates collaboration between biological, clinical, and systems biology researchers.
  • Enables extrapolation from single-cell data to complex multicellular system dynamics and hypothesis generation.