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dc.contributor.authorKim, Min-Cheol
dc.contributor.authorAsada, H. Harry
dc.date.accessioned2020-04-01T13:17:46Z
dc.date.available2020-04-01T13:17:46Z
dc.date.issued2019-09-20
dc.identifier.issn1553-7358
dc.identifier.urihttps://hdl.handle.net/1721.1/124472
dc.description.abstractCells interacting through an extracellular matrix (ECM) exhibit emergent behaviors resulting from collective intercellular interaction. In wound healing and tissue development, characteristic compaction of ECM gel is induced by multiple cells that generate tensions in the ECM fibers and coordinate their actions with other cells. Computational prediction of collective cell-ECM interaction based on first principles is highly complex especially as the number of cells increase. Here, we introduce a computationally-efficient method for predicting nonlinear behaviors of multiple cells interacting mechanically through a 3-D ECM fiber network. The key enabling technique is superposition of single cell computational models to predict multicellular behaviors. While cell-ECM interactions are highly nonlinear, they can be linearized accurately with a unique method, termed Dual-Faceted Linearization. This method recasts the original nonlinear dynamics in an augmented space where the system behaves more linearly. The independent state variables are augmented by combining auxiliary variables that inform nonlinear elements involved in the system. This computational method involves a) expressing the original nonlinear state equations with two sets of linear dynamic equations b) reducing the order of the augmented linear system via principal component analysis and c) superposing individual single cell-ECM dynamics to predict collective behaviors of multiple cells. The method is computationally efficient compared to original nonlinear dynamic simulation and accurate compared to traditional Taylor expansion linearization. Furthermore, we reproduce reported experimental results of multi-cell induced ECM compaction.en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant CMMI-1762961)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant CBET-0939511)en_US
dc.language.isoen
dc.publisherPublic Library of Science (PLoS)en_US
dc.relation.isversionof10.1371/journal.pcbi.1006798en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourcePLoSen_US
dc.subjectEcologyen_US
dc.subjectModelling and Simulationen_US
dc.subjectComputational Theory and Mathematicsen_US
dc.subjectGeneticsen_US
dc.subjectEcology, Evolution, Behavior and Systematicsen_US
dc.subjectMolecular Biologyen_US
dc.subjectCellular and Molecular Neuroscienceen_US
dc.titleMulti-cell ECM compaction is predictable via superposition of nonlinear cell dynamics linearized in augmented state spaceen_US
dc.typeArticleen_US
dc.identifier.citationMayalu, Michaëlle N., Min-Cheol Kim and H. Harry Asada. "Multi-cell ECM compaction is predictable via superposition of nonlinear cell dynamics linearized in augmented state space." PLoS one 15 (2019): e1006798 © 2019 The Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.relation.journalPLoS oneen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2020-02-10T20:12:46Z
dspace.date.submission2020-02-10T20:12:49Z
mit.journal.volume15en_US
mit.journal.issue9en_US
mit.licensePUBLISHER_CC


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