2018
Manifold learning-based methods for analyzing single-cell RNA-sequencing data
Moon K, Stanley J, Burkhardt D, van Dijk D, Wolf G, Krishnaswamy S. Manifold learning-based methods for analyzing single-cell RNA-sequencing data. Current Opinion In Systems Biology 2018, 7: 36-46. DOI: 10.1016/j.coisb.2017.12.008.Peer-Reviewed Original ResearchSingle-cell RNA-sequencing dataSingle-cell RNA sequencing technologyRNA sequencing technologyRNA-sequencing dataThousands of cellsGene regulationCellular statesPhenotypic diversityCellular developmentGene interactionsSequencing technologiesGene expressionSeq dataUnderlying biological signalManifold learning-based methodsSingle experimentBiological signalsRecent advancesDiversityDeeper insightRegulationExpression
2016
Large-scale mapping of gene regulatory logic reveals context-dependent repression by transcriptional activators
van Dijk D, Sharon E, Lotan-Pompan M, Weinberger A, Segal E, Carey LB. Large-scale mapping of gene regulatory logic reveals context-dependent repression by transcriptional activators. Genome Research 2016, 27: 87-94. PMID: 27965290, PMCID: PMC5204347, DOI: 10.1101/gr.212316.116.Peer-Reviewed Original ResearchConceptsTranscription factorsGene regulatory logicPromoter DNA sequencesGene expression outputActive transcription factorTarget gene expressionGene expression profilesMaximum promoter activityTranscriptional activatorExpression outputRegulatory logicDNA sequencesGene expressionPromoter activityIntracellular signalsExpression profilesTF moleculesActivity of thousandsActivator siteLocal poolAbsolute expressionTF concentrationPromoterKey mediatorExpression