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dc.contributor.authorBelyaeva, Anastasiya
dc.contributor.authorKubjas, Kaie
dc.contributor.authorSun, Lawrence J
dc.contributor.authorUhler, Caroline
dc.date.accessioned2022-07-21T13:50:11Z
dc.date.available2022-07-21T13:50:11Z
dc.date.issued2022
dc.identifier.urihttps://hdl.handle.net/1721.1/143918
dc.language.isoen
dc.publisherSociety for Industrial & Applied Mathematics (SIAM)en_US
dc.relation.isversionof10.1137/21M1390372en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceSIAMen_US
dc.titleIdentifying 3D Genome Organization in Diploid Organisms via Euclidean Distance Geometryen_US
dc.typeArticleen_US
dc.identifier.citationBelyaeva, Anastasiya, Kubjas, Kaie, Sun, Lawrence J and Uhler, Caroline. 2022. "Identifying 3D Genome Organization in Diploid Organisms via Euclidean Distance Geometry." SIAM Journal on Mathematics of Data Science, 4 (1).
dc.contributor.departmentMassachusetts Institute of Technology. Laboratory for Information and Decision Systems
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Society
dc.relation.journalSIAM Journal on Mathematics of Data Scienceen_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.updated2022-07-21T13:46:11Z
dspace.orderedauthorsBelyaeva, A; Kubjas, K; Sun, LJ; Uhler, Cen_US
dspace.date.submission2022-07-21T13:46:12Z
mit.journal.volume4en_US
mit.journal.issue1en_US
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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