2011
Modeling the effector - regulatory T cell cross-regulation reveals the intrinsic character of relapses in Multiple Sclerosis
Vélez de Mendizábal N, Carneiro J, Solé R, Goñi J, Bragard J, Martinez-Forero I, Martinez-Pasamar S, Sepulcre J, Torrealdea J, Bagnato F, Garcia-Ojalvo J, Villoslada P. Modeling the effector - regulatory T cell cross-regulation reveals the intrinsic character of relapses in Multiple Sclerosis. BMC Systems Biology 2011, 5: 114. PMID: 21762505, PMCID: PMC3155504, DOI: 10.1186/1752-0509-5-114.Peer-Reviewed Original ResearchConceptsCross-regulationT cellsAutoimmune diseasesImmune systemMultiple sclerosisEffector T cellsRegulatory T cellsT cell memoryTissue damageEffects of such therapyPathogenesis of autoimmune diseasesT cell activationPredicting disease courseModulating effectorsBiological knowledgeMolecular mechanismsIrreversible tissue damageClinical relapseStochastic eventsRegulatory populationsCentral toleranceAutoimmune activityDisease courseNegative feedbackEffector
2010
Messenger RNA fluctuations and regulatory RNAs shape the dynamics of a negative feedback loop
Martínez M, Soriano J, Tlusty T, Pilpel Y, Furman I. Messenger RNA fluctuations and regulatory RNAs shape the dynamics of a negative feedback loop. Physical Review E 2010, 81: 031924. PMID: 20365787, DOI: 10.1103/physreve.81.031924.Peer-Reviewed Original ResearchConceptsSingle-cell levelRegulatory RNAsGene expression variabilityIndividual cellsPost-transcriptional regulationNoncoding regulatory RNAsCell population levelNegative feedback loopSingle-cell experimentsRegulatory networksRNA transcriptsRepress translationRegulatory transcriptsPost-transcriptionallyExpression variabilityRNAStochastic eventsMessenger RNATranscriptionProtein expressionMessengerCell populationsPopulation levelCellsFeedback loop
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