Daniel E. Zak, Mammalian Systems Biology, Ogunnaike Group

Daniel E. Zak, Mammalian Systems Biology, Ogunnaike Group

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Daniel E. Zak Mammalian Systems Biology
zak@che.udel.edu *Curriculum Vitae* (faculty search) *Curriculum Vitae* (post-doc)		Ph.D., 2000-2005 University of Delaware, Department of Chemical Engineering in collaboration with: Thomas Jefferson University, Daniel Baugh Institute for Functional Genomics and Computational Biology M.S., 1998-2000 University of Illinois, Urbana-Champaign, Department of Chemical Engineering in collaboration with: National University of Singapore, Department of Chemical Engineering B.S., 1993-1998 University of Illinois, Urbana-Champaign, Department of Chemical Engineering
Research interests			How do mammalian cells change themselves in response to external signals? The objective of my research is to develop system-wide computational models of this extraordinarily complex and physiologically important process, taking advantage of the wealth of biochemical information available and the opportunities provided by the omics data revolution. This has involved the development of a structured modeling approach to integrate diverse data types. My experimental systems of interest are EGFR signaling in liver and neuromodulation in the suprachiasmatic nucleus. For a detailed discussion of all of my research activities, please follow this link.
Publications			Zak DE, Vadigepalli R, Gonye GE, Doyle FJ 3rd, Schwaber JS, Ogunnaike BA. Unconventional systems analysis problems in molecular biology: a case study in gene regulatory network modeling. Computers and Chemical Engineering. In Press. [Abstract-PDF] [Supplementary Material] Zak DE, Stelling J, Doyle FJ 3rd. Sensitivity analysis of oscillatory (bio)chemical systems. Computers and Chemical Engineering. In Press. [Abstract-PDF] Zak DE, Pearson RK, Vadigepalli R, Gonye GE, Schwaber JS, Doyle FJ 3rd. Continuous-time identification of gene expression models. OMICS. 2003, 7(4):373-86. [Abstract] [PDF] [Supplementary Material] Zak DE, Gonye GE, Schwaber JS, Doyle FJ 3rd. Importance of input perturbations and stochastic gene expression in the reverse engineering of genetic regulatory networks: insights from an identifiability analysis of an in silico network. Genome Research. 2003 Nov;13(11):2396-405. [Abstract] [FullText] [PDF] [Supplementary Material] [Model Files] Vadigepalli R, Chakravarthula P, Zak DE, Schwaber JS, Gonye GE. PAINT: a promoter analysis and interaction network generation tool for gene regulatory network identification. OMICS, 2003;7(3):235-52. [Abstract] [PDF] [PAINT]
Conference proceedings			Zak DE, Doyle FJ, Vlachos DG and Schwaber JS. "Stochastic kinetic analysis of transcriptional feedback models for circadian rhythms." Proceedings of the 40th IEEE Conference on Decision and Control. 849-854, 2001. [PDF] Zak DE, Doyle FJ, Gonye GE and Schwaber JS. "Simulation studies for the identification of genetic networks from cDNA array and regulatory activity data." Proceedings of the Second International Conference on Systems Biology. 231-238, 2001. [PDF] [Model Files] Markevich N, Kiyatikin AB, Zak DE, Pastorino JG, Hoek JB, and Kholodenko BN. "Four-dimensional organization of cellular signal transduction cascades." Proceedings of the Second International Conference on Systems Biology. 141-147, 2001. [PDF]
Conference presentations			For a complete list of my conference presentations and their respective abstracts, please follow this link.

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Last update: 03/26/2005

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