Associate ProfessorPhone Number: 402.826.8658
Credentials: BS, PHD
B.S. in Applied Mathematics
The University of Tulsa, 2007
Ph.D. in Bioinformatics and Computational Biology
Iowa State University, 2013
BIO 110: Inquiry Lab (SEA-PHAGES), BIO 111: Energy of Life Cells to Ecosystems, BIO 316: Introduction to Computational Biology, BIO 271: Phage Genome Annotation, BIO 352: Genetics and Functional Genomics, Biology Research I/II/III
My teaching interests center on introducing computational and mathematical thinking into the core Biology curriculum. The recent explosion of gene and genome sequence data has made it impossible for biologists to effectively mine all of the available data without the aid of computers and sophisticated mathematical models! My goal is to help my students understand the importance of mathematics, computer science, and statistics to modern biology. In addition to developing classroom activities to give students hands-on experience using common computational tools and biological databases, I hope to interest students in the algorithms and models that make these tools work. I am also interested in developing stand-alone upper level courses in bioinformatics, computational biology, and genetics/genomics that would allow students to explore this kind of science in an in-depth way.
My previous research has focused on the analysis of whole genome sequences to identify binding sites for a specific type of DNA binding protein called a TAL effector. TAL effectors come from bacteria that cause diseases in a variety of economically important crops, and understanding how these proteins bind to DNA has implications for understanding crop diseases and disease resistance. TAL effector nucleases can also be used for editing DNA sequences in living cells and organisms, making them potentially useful in genome engineering applications and for therapies for genetic diseases. My research program at Doane builds on my experience in analyzing genome sequence data for TAL effector binding sites, and in using genome sequence data to understand crop disease resistance. In addition to sequence analysis, my lab has also begun to delve in to computer-based image analysis and phenotyping. More generally, research in my lab allows students to gain experience using computational approaches to generate experimentally testable hypotheses and then use those experimental results to refine computational models of biological processes.
RESEARCH COLLABORATIONS AND OTHER PROJECTS
Center for Root and Rhizobiome (CRRI)
Publications (Published while at Doane)
Doyle, E.L., Fillman, C.L., Reyna, N.S., Tobiason, D.M., Westholm, D.E., et al. Genome Sequences of Four Cluster P Mycobacteriophages (2018). Genome Announcements, 6, 2. Includes 11 Doane undergraduate students as co-authors.
Perez-Quintero, A.L., Lamy, L., Zarate, C.A., Cunnac, S., Doyle, E.L., Bogdanove, A.J., Szurek, B., and Dereeper, A. (2017) DaTALbase: A Database for Genomic and Transcriptomic Data Related to TAL Effectors. Molecular Plant Microbe Interactions, doi: 10.1094.
Meysenburg, M., Durham Brooks T., Burks, R., Doyle E., Frye T. (2018) DIVAS: Outreach to the Natural Sciences through Image Processing. Proceedings of the 2018 ACM SIGCSE Technical Symposium on Computer Science Education, ACM.
Doan, T.H.,* Doan, T.A., Kangas, M.J., Ernest, A.E.,* Tran, D.,* Wilson, C.L., Holmes, A.E., Doyle, E.L., and Durham Brooks, T.L. (2017) A low-cost imaging method for the temporal and spatial colorimetric detection of free amines on maize root surfaces. Frontiers in Plant Science, 8, 1513. * indicates an undergraduate co-author.
Wang, L., F. C. Rinaldi, P. Singh, E. L. Doyle, Z. E. Dubrow, T. T. Tran, A. L. Perez-Quintero, B. Szurek, and A. J. Bogdanove. (2017) Tal Effectors Drive Transcription Bidirectionally in Plants. Molecular Plant 10, 285-96.
Cernadas, R.A., Doyle, E.L., Niño –Liu, D.O., Wilkins, K.E., Bancroft, T., Wang, L., Schmidt, C.L., Caldo, R.A., Yang, B., White, F.F., Nettleton, D., Wise, R.P., and Bogdanove, A.J. (2014). Code-assisted discovery of TAL effector targets in bacterial leaf streak of rice reveals contrast with bacterial blight and a novel susceptibility gene. PLoS Pathogens, 10, e1003972.
Doyle, E.L., Hummel, A.W., Demorest, Z.L., Starker, C.G., Voytas, D.F., Bradley, P., and Bogdanove, A.J. (2013) TAL Effector specificity for base 0 of the DNA target is altered in a complex, effector- and assay-dependent manner by substitutions for the tryptophan in cryptic repeat –1. PLoS One, 8, e82120.
Doyle, E.L., Stoddard, B.L., Voytas, D.F., and Bogdanove, A.J. (2013). TAL effectors: highly adaptable phytobacterial virulence factors and readily engineered DNA targeting proteins. Trends in Cell Biology, 23, 390-398.
Hummel, A.W., Doyle, E.L. and Bogdanove, A.J. (2012) Addition of transcription activator-like effector binding sites to a pathogen strain-specific rice bacterial blight resistance gene makes it effective against additional strains and against bacterial leaf streak. The New Phytologist, 195, 883-893.
Doyle, E.L., Booher, N.J., Standage, D.S., Voytas, D.F., Brendel, V.P., VanDyk, J.K. and Bogdanove, A.J. (2012) TAL Effector-Nucleotide Targeter (TALE-NT) 2.0: tools for TAL effector design and target prediction. Nucleic Acids Research, 40, W117-W122.
Cermak, T.*, Doyle, E.L.* (*co-first authors), Christian, M., Wang, L., Zhang, Y., Schmidt, C., Baller, J.A., Somia, N.V., Bogdanove, A.J. and Voytas, D.F. (2011) Efficient design and assembly of custom TALEN and other TAL effector-based constructs for DNA targeting. Nucleic Acids Research, 39, e82.
Vendettuoli, M., Doyle, E. and Hofmann, H. (2011) In Arabnia, H. R. and Tran, Q. N. (eds.), Software Tools and Algorithms for Biological Systems. Springer-Verlag Berlin, pp. 145-153.
Christian, M., Cermak, T., Doyle, E.L., Schmidt, C., Zhang, F., Hummel, A., Bogdanove, A.J. and Voytas, D.F. (2010) Targeting DNA double-strand breaks with TAL effector nucleases. Genetics, 186, 757-761.