Bernie J. Daigle, Jr., Ph.D.

Bernie J. Daigle, Jr., Ph.D.

Assistant Professor, Departments of Biological Sciences and Computer Science

Phone
901.678.2727
Fax
901.678.4457
Office
J. M. Smith Hall 402C, Memphis, TN 38152
Office Hours
By Appointment

About Dr. Daigle

Dr. Daigle joined the Department in 2015. He received his B.S. in Biology from Cornell University with a concentration in Genetics and Development. His Ph.D. research at Stanford University focused on developing and applying bioinformatics tools that integrate biological knowledge with transcriptomics data. In his postdoctoral work, conducted at the University of California, Santa Barbara, Dr. Daigle continued his bioinformatics research while also beginning projects focused on modeling and analysis of stochastic biochemical systems. At the University of Memphis, Dr. Daigle conducts research in both areas. Current projects in his lab involve the integration of genome-scale datasets to identify biomarkers for human disease and the application of computational methods for characterizing promoter architecture from single-cell gene expression data. In addition to his primary appointment in the Department of Biological Sciences, Dr. Daigle has a secondary appointment in the Department of Computer Science and is a faculty affiliate with the Bioinformatics Program.

Research Interests

  • Genomic data integration
  • Bioinformatics
  • Single-cell gene expression
  • Computational Systems Biology
  • Software development

Education

B.S. Biology, Cornell University; Ph.D. Genetics, Stanford University; Postdoctoral researcher Computer Science, University of California, Santa Barbara

Recent Publications

  • Daigle Jr., B.J., Soltani, M., Petzold, L.R., and Singh, A. (2015). Inferring single-cell gene expression mechanisms using stochastic simulation. Bioinformatics 31, 1428–1435.

  • Thakur, G.S., Daigle Jr., B.J., Dean, K.R., Zhang, Y., Rodriguez-Fernandez, M., Hammamieh, R., Yang, R., Jett, M., Palma, J., Petzold, L.R., et al. (2015). Systems biology approach to understanding post-traumatic stress disorder. Mol. BioSyst. 11, 980–993.

  • Petzold, L., Zhang, Y., Daigle Jr., B.J., Ferrigno, L., and Cohen, M. (2013). Toward a data-driven model of trauma dynamics. Journal of Critical Care 28, e37.

  • Yang, R.*, Daigle Jr., B.J.*, Muhie, S.Y., Hammamieh, R., Jett, M., Petzold, L., and Doyle III, F.J. (2013). Core modular blood and brain biomarkers in social defeat mouse model for post traumatic stress disorder. BMC Systems Biology 7, 80. *Contributed equally.

  • White, R.E., Palm, C., Xu, L., Ling, E., Ginsburg, M., Daigle Jr., B.J., Han, R., Patterson, A., Altman, R.B., and Giffard, R.G. (2012). Mice Lacking the β2 Adrenergic Receptor Have a Unique Genetic Profile before and after Focal Brain Ischaemia. ASN Neuro 4, AN20110020.

  • Daigle Jr., B.J., Roh, M.K., Petzold, L.R., and Niemi, J. (2012). Accelerated maximum likelihood parameter estimation for stochastic biochemical systems. BMC Bioinformatics 13, 68.

  • Yang, R.*, Daigle Jr., B.J.*, Petzold, L.R., and Doyle, F.J. (2012). Core module biomarker identification with network exploration for breast cancer metastasis. BMC Bioinformatics 13, 12. *Contributed equally.

  • Roh, M.K.*, Daigle Jr., B.J.*, Gillespie, D.T., and Petzold, L.R. (2011). State-dependent doubly weighted stochastic simulation algorithm for automatic characterization of stochastic biochemical rare events. The Journal of Chemical Physics 135, 234108. *Contributed equally.

  • Daigle Jr., B.J.*, Roh, M.K.*, Gillespie, D.T., and Petzold, L.R. (2011). Automated estimation of rare event probabilities in biochemical systems. The Journal of Chemical Physics 134, 044110. *Contributed equally.

  • Daigle Jr., B.J., Deng, A., McLaughlin, T., Cushman, S.W., Cam, M.C., Reaven, G., Tsao, P.S., and Altman, R.B. (2010). Using Pre-existing Microarray Datasets to Increase Experimental Power: Application to Insulin Resistance. PLoS Comput Biol 6, e1000718.