2013
Promoter Sequence Determines the Relationship between Expression Level and Noise
Carey LB, van Dijk D, Sloot PM, Kaandorp JA, Segal E. Promoter Sequence Determines the Relationship between Expression Level and Noise. PLOS Biology 2013, 11: e1001528. PMID: 23565060, PMCID: PMC3614515, DOI: 10.1371/journal.pbio.1001528.Peer-Reviewed Original ResearchMeSH KeywordsAlcohol DehydrogenaseBacterial ProteinsBase SequenceBinding SitesCation Transport ProteinsEnzyme InductionGene ExpressionGene Expression Regulation, FungalGene LibraryGenes, ReporterKineticsLuminescent ProteinsModels, GeneticPromoter Regions, GeneticProtein BindingSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsTranscription FactorsConceptsTranscriptional burstsUnique transcriptional statesTranscription factor activitySingle target geneExpression levelsMechanism of repressionAbility of cellsTF activityGene expression levelsExtracellular cuesTranscriptional statesTranscriptional regulationPromoter DNAPromoter sequencesSingle TFCell variabilityTarget genesRegulatory mechanismsExpression changesZap1Diverse mechanismsNative targetsFactor activityExpression increasesGenesTwo 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
2010
Inference of Surface Membrane Factors of HIV-1 Infection through Functional Interaction Networks
Jaeger S, Ertaylan G, van Dijk D, Leser U, Sloot P. Inference of Surface Membrane Factors of HIV-1 Infection through Functional Interaction Networks. PLOS ONE 2010, 5: e13139. PMID: 20967291, PMCID: PMC2953485, DOI: 10.1371/journal.pone.0013139.Peer-Reviewed Original ResearchConceptsSurface membrane proteinsMembrane factorsBioinformatics techniquesNovel cell surface proteinCell/tissue typesSurface proteinsFunctional interaction networkDifferent cell/tissue typesSimilar cellular processesCell surface proteinsCellular surface proteinsCellular processesMembrane proteinsInteraction networksFunctional similarityCell typesCommon functionPatient-specific disease progressionDirect interactionProteinSpecific disease progressionTissue typesExcellent targetNetwork centrality analysisComprehensive network