
TL;DR
This paper explores different modeling approaches for cellular metabolism in populations, comparing lumped and individual models, and proposes an intermediate granularity model to balance detail and simplicity.
Contribution
It introduces a two-lump tissue interaction model as an effective intermediate approach for population metabolism modeling.
Findings
Two-lump model captures key dynamics better than single lump models.
Modeling at intermediate granularity preserves important individual behaviors.
The approach offers a balance between detail and computational efficiency.
Abstract
We investigate methods for modelling metabolism within populations of cells. Typically one represents the interaction of a cloned population of cells with their environment as though it were one large cell. The question is as to whether any dynamics are lost by this assumption, and as to whether it might be more appropriate to instead model each cell individually. We show that it is sufficient to model at an intermediate level of granularity, representing the population as two interacting lumps of tissue.
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Taxonomy
TopicsMicrobial Metabolic Engineering and Bioproduction · Gene Regulatory Network Analysis · Mathematical Biology Tumor Growth
