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A Discretized Overlap Resolution Algorithm (DORA) for resolving spatial overlaps in individual-based models of

Ihab Hashem¹, Jian Wang¹, Jan F M Van Impe¹

¹KU Leuven, Chemical Engineering Department, BioTeC & OPTEC, Ghent, Belgium.

Plos Computational Biology

|April 21, 2025

Summary

Individual-based modeling (IbM) for microbial growth is computationally intensive. A new Discretized Overlap Resolution Algorithm (DORA) significantly improves efficiency for simulating large microbial populations.

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Area of Science:

Microbial Ecology
Biochemical Engineering
Computational Biology

Background:

Individual-based modeling (IbM) simulates spatial microbial growth but faces computational challenges.
Resolving spatial overlaps between individual cells is a major bottleneck in traditional IbM methods.

Purpose of the Study:

To introduce a novel algorithm, the Discretized Overlap Resolution Algorithm (DORA), to enhance the computational efficiency of IbM.
To overcome the limitations of traditional pairwise comparison methods for managing cell overlaps in large populations.

Main Methods:

DORA employs a grid-based framework to discretize simulation space and assign cells to grid units.
This transforms computationally intensive pairwise comparisons into efficient grid-based operations.

Main Results:

DORA significantly reduces computational load, especially for large microbial populations.
Simulations demonstrate DORA's superior efficiency and accuracy in capturing microbial growth dynamics compared to conventional methods.

Conclusions:

DORA enables efficient modeling of densely populated microbial communities within practical timeframes.
The algorithm expands the scope and applicability of individual-based modeling for microbial systems.