0B68 Schwaber, James S. - Thomas Jefferson University - Thomas Jefferson University
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James S. Schwaber, PhD

Contact Dr. Schwaber

1020 Locust Street
Jefferson Alumni Hall, Suite 314D
Philadelphia, PA 19107

(215) 503-7823

Most Recent Peer-reviewed Publications

  1. Inputs drive cell phenotype variability
  2. What is it to be Conscious?
  3. Coordinated Dynamic Gene Expression Changes in the Central Nucleus of the Amygdala During Alcohol Withdrawal
  4. Dynamic transcriptomics: Transcriptomic discovery of a biological multiple-input multiple-output heart control mechanism
  5. Rapid Temporal Changes in the Expression of a Set of Neuromodulatory Genes During Alcohol Withdrawal in the Dorsal Vagal Complex: Molecular Evidence of Homeostatic Disturbance
  6. Integrative gene regulatory network analysis reveals light-induced regional gene expression phase shift programs in the mouse suprachiasmatic nucleus
  7. Temporal changes in innate immune signals in a rat model of alcohol withdrawal in emotional and cardiorespiratory homeostatic nuclei
  8. Adaptive transcriptional dynamics of A2 neurons and central cardiovascular control pathways
  9. The neuroscience-systems biology disconnect: Towards the NeuroPhysiome
  10. Robust dynamic balance of AP-1 transcription factors in a neuronal gene regulatory network
  11. Cellular-signaling pathway signatures
  12. The effect of biological variability on the angiotensin II gene regulatory network in the central regulation of blood pressure
  13. Elucidating the transcriptional regulatory network underlying the Nts response to acute hypertension
  14. A control system hypothesis of the N-methyl-D-aspartate glutamate receptor's role in alcoholism and
  15. Modeling the control of an excitatory neurotransmitter receptor during alcoholism and alcohol withdrawal
  16. A fast carrier chromatin immunoprecipitation method applicable to microdissected tissue samples
  17. Dynamic transcriptomic response to acute hypertension in the nucleus tractus solitarius
  18. From promoter analysis to transcriptional regulatory network prediction using PAINT.
  19. Epidermal growth factor receptor-induced circadian-time-dependent gene regulation in suprachiasmatic nucleus
  20. Quantifying gene network connectivity in silico: Scalability and accuracy of a modular approach
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