2021
Quantifying the effect of experimental perturbations at single-cell resolution
Burkhardt DB, Stanley JS, Tong A, Perdigoto AL, Gigante SA, Herold KC, Wolf G, Giraldez AJ, van Dijk D, Krishnaswamy S. Quantifying the effect of experimental perturbations at single-cell resolution. Nature Biotechnology 2021, 39: 619-629. PMID: 33558698, PMCID: PMC8122059, DOI: 10.1038/s41587-020-00803-5.Peer-Reviewed Original ResearchConceptsSingle-cell RNA sequencing datasetsClusters of cellsRNA sequencing datasetsSingle-cell resolutionSingle-cell levelTranscriptomic spaceSequencing datasetsExperimental perturbationsCell populationsGene signatureVertex frequencyDiscrete regionsCellsEffects of perturbationsMultiple conditionsPerturbation responseClustersPopulationPerturbationsLikelihood estimatesGraph signal processing
2013
Two DNA-encoded strategies for increasing expression with opposing effects on promoter dynamics and transcriptional noise
Dadiani M, van Dijk D, Segal B, Field Y, Ben-Artzi G, Raveh-Sadka T, Levo M, Kaplow I, Weinberger A, Segal E. Two DNA-encoded strategies for increasing expression with opposing effects on promoter dynamics and transcriptional noise. Genome Research 2013, 23: 966-976. PMID: 23403035, PMCID: PMC3668364, DOI: 10.1101/gr.149096.112.Peer-Reviewed Original ResearchConceptsPromoter dynamicsExpression variabilityPromoter transitionsSingle-cell time-lapse microscopyInactive stateSequence changesNucleosome-disfavoring sequencesCis-regulatory elementsProcess of transcriptionActive stateNumber of transcriptsTime-lapse microscopyCell populationsTranscriptional noiseTranscriptional dynamicsSite resultsTranscription factorsDNA sequencesGene expressionMean expressionIdentical populationsIndividual cellsSequence resultsExpression levelsTranscripts