Evidence map›Paper›PMID 42698041›Full record

ArticleBulletin of mathematical biology2026

Algebraic Representation of Mitochondrial Dynamics.

Raphael Mostov, Greyson Lewis, Gabriel Sturm, Wallace F Marshall

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Raphael MostovDepartment Biochemistry and Biophysics, University of California, San Francisco, USA.
Greyson LewisDepartment Biochemistry and Biophysics, University of California, San Francisco, USA.
Gabriel SturmDepartment Biochemistry and Biophysics, University of California, San Francisco, USA.
Wallace F MarshallDepartment Biochemistry and Biophysics, University of California, San Francisco, USA. wallace.marshall@ucsf.edu.ORCID http://orcid.org/0000-0002-8467-5763

Funding

Origins of Cell GeometryR35GM130327 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Wallace Marshall · 2019 to 2026
$5.3M
National Science Foundation DBI1548297NIGMS NIH HHS R35 GM130327
6 · The paper itself

Abstract

This paper addresses the increasing need for comprehensive mathematical descriptions of cell organization by examining the algebraic structure of mitochondrial network dynamics. Mitochondria are cellular structures involved in metabolism that take the form of a network of membrane-based tubes that undergo continuous re-arrangement by a set of morphological processes, including fission and fusion, carried out by protein-based machinery. Because of their network structure, mitochondria can be represented as graphs, and the morphological operations that take place in the cell, referred to as mitochondrial dynamics, can be represented by changes to the graphs. Prior studies have classified mitochondrial graphs based on graph-theoretic features, but an alternative approach is to focus not on the graphs themselves but on the set of morphological operations inducing mitochondrial dynamics, since this may provide a simpler representation. Moreover, the operations are what determine the graphs that will be generated in a biological system. Here we show that mitochondrial dynamics give rise to a category in which the objects are equivalence classes of graphs defined by one of the morphological operations and morphisms are mappings between these equivalence classes defined by the remaining morphological operations. For mitochondria consisting of a single component this gives rise to a particularly simple representation. Using these formalisms we define a distance metric for similarity between mitochondrial structures based on an edit distance, and demonstrate how this representation can be used for visualization and statistical analysis of biological data. In the course of defining these structures we provide a mathematical motivation for new experimental questions regarding mitochondrial fusion, the impacts of cell division on mitochondrial morphology, and the presence of a single giant component in some cell types. This work points to a general strategy for formulating a cell structure state-space, based not on the shapes of cellular structures, but on relations between the dynamic operations that produce them.

Indexed as

MitochondriaMitochondrial DynamicsModels, BiologicalAnimalsMathematical ConceptsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsSaccharomyces cerevisiae ProteinsAlgebraic graph theoryBudding yeastCell representationMitochondrial fissionMitochondrial fusionMorpholomicsPlanar graphsSpatial statistics

Identifiers

PMID42698041
PMCPMC13545136

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.