2021
Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks
Sehanobish A, Ravindra N, Van Dijk D. Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks. Proceedings Of The AAAI Conference On Artificial Intelligence 2021, 35: 4864-4873. DOI: 10.1609/aaai.v35i6.16619.Peer-Reviewed Original ResearchSARS-CoV-2 infectionSingle-cell omics dataCOVID-19 severitySingle-cell RNA sequencing datasetsCell typesRNA sequencing datasetsSARS-CoV-2Transcriptomic patternsSequencing datasetsOmics dataCellular determinantsCellular understandingIndividual cellsBronchoalveolar lavage fluid samplesInfected cellsSevere COVID-19Lavage fluid samplesCOVID-19Lung organoidsDisease statesInfectionTranscriptomeCellsSeverityFluid samples
2015
Slow-growing cells within isogenic populations have increased RNA polymerase error rates and DNA damage
van Dijk D, Dhar R, Missarova AM, Espinar L, Blevins WR, Lehner B, Carey LB. Slow-growing cells within isogenic populations have increased RNA polymerase error rates and DNA damage. Nature Communications 2015, 6: 7972. PMID: 26268986, PMCID: PMC4557116, DOI: 10.1038/ncomms8972.Peer-Reviewed Original ResearchConceptsTranscriptional stress responseDNA damageDNA damage responseIsogenic populationsRNA polymerase fidelityDamage responseTranscriptional differencesIsogenic cellsEnvironmental stressCell variabilityStress responseGrowth ratePolymerase fidelityCulture conditionsPolymerase error rateOxidative stressCellsSuch cellsSame environmentTranscriptomeTransposonSubpopulationsTranscriptsGenotypicStress