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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.<\/jats:p>","DOI":"10.1007\/s11538-026-01738-9","type":"journal-article","created":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T17:39:07Z","timestamp":1788543547000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Algebraic Representation of Mitochondrial Dynamics"],"prefix":"10.1007","volume":"88","author":[{"given":"Raphael","family":"Mostov","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Greyson","family":"Lewis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gabriel","family":"Sturm","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8467-5763","authenticated-orcid":false,"given":"Wallace F.","family":"Marshall","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,4]]},"reference":[{"key":"1738_CR1","doi-asserted-by":"publisher","unstructured":"Aliakbary S, Habibi J, Movaghar A (2013) Quantification and comparison of degree distributions in complex networks. https:\/\/doi.org\/10.48550\/arXiv.1307.3625. arXiv:1307.3625","DOI":"10.48550\/arXiv.1307.3625"},{"key":"1738_CR2","doi-asserted-by":"publisher","unstructured":"Bagheri N et al (2022) The new era of quantitative cell imaging-challenges and opportunities. 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