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dc.contributor.authorMohammadi, Shahin
dc.contributor.authorDavila Velderrain, Jose
dc.contributor.authorKellis, Manolis
dc.date.accessioned2021-01-12T22:47:03Z
dc.date.available2021-01-12T22:47:03Z
dc.date.issued2019-12
dc.date.submitted2019-07
dc.identifier.issn2405-4712
dc.identifier.urihttps://hdl.handle.net/1721.1/129394
dc.description.abstractThe human interactome is instrumental in the systems-level study of the cell and the contextualization of disease-associated gene perturbations. However, reference organismal interactomes do not capture the cell-type-specific context in which proteins and modules preferentially act. Here, we introduce SCINET, a computational framework that reconstructs an ensemble of cell-type-specific interactomes by integrating a global, context-independent reference interactome with a single-cell gene-expression profile. SCINET addresses technical challenges of single-cell data by robustly imputing, transforming, and normalizing the initially noisy and sparse expression of data. Inferred cell-level gene interaction probabilities and group-level interaction strengths define cell-type-specific interactomes. We use SCINET to reconstruct and analyze interactomes of the major human brain and immune cell types, revealing specificity and modularity of perturbations associated with neurodegenerative, neuropsychiatric, and autoimmune disorders. We report cell-type interactomes for brain and immune cell types, together with the SCINET package.en_US
dc.description.sponsorshipNIH (Grants U01-MH119509, R01-AG062335, RF1-AG054012, and U01-NS110453)en_US
dc.language.isoen
dc.publisherElsevier BVen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.cels.2019.10.007en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceElsevieren_US
dc.titleReconstruction of Cell-type-Specific Interactomes at Single-Cell Resolutionen_US
dc.typeArticleen_US
dc.identifier.citationMohammadi, Shahin et al. "Reconstruction of Cell-type-Specific Interactomes at Single-Cell Resolution." Cell Systems 9, 6 (December 2019): P559-568.e4 © 2019 The Authorsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalCell Systemsen_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.updated2021-01-05T18:34:06Z
dspace.orderedauthorsMohammadi, S; Davila-Velderrain, J; Kellis, Men_US
dspace.date.submission2021-01-05T18:34:10Z
mit.journal.volume9en_US
mit.journal.issue6en_US
mit.licensePUBLISHER_CC
mit.metadata.statusComplete


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