Regulatory DNA encodes the gene regulatory networks that are required for virtually every process in an animal, from development to immunity. The Wunderlich lab is interested in understanding how a gene regulatory network's tasks influence its architecture, robustness, and evolvability. To probe these questions, we use two model systems: the Drosophila early embryonic patterning system and the Drosophila innate immune response. In both systems, we pair imaging-based and genomic measurements of gene expression with statistical and physically-based computational models to explore questions of gene regulatory network function. We exploit naturally-occuring sequence variation between individuals and species as a tool to measure how changes in regulatory DNA affect transcriptional regulation.
The Wunderlich lab is looking for enthusiastic students and post docs to join the lab.
We are accepting applications for a postdoc position in the lab and welcome candidates who are interested in understanding the function of regulatory DNA using a combination of experimental and computational approaches. Applicants can send a CV and cover letter describing your previous research experience and future research interests, including why you are interested in the lab, to Zeba.
Undergraduates interested in computational studies of gene regulation in the embryo should contact Zeba to discuss possible projects.
PhD, Harvard University, Biophysics, 2008
BA, Molecular Biology & Biochemistry, Statistics, Rutgers University, 2003
BS, Bioengineering, Caltech, 2013
BS, Microbiology, SDSU, 2015
BS, Genetics, UC Davis, 2013
Undergraduate Student, Genetics and Anthropology, 2015-2016
MV Staller, D Yan, S Randklev, MD Bragdon, Z Wunderlich, R Tao, LA Perkins, AH DePace, N Perrimon. Genetics. (2013).
Z Wunderlich, MD Bragdon, K Eckenrode, T Martin, S Pearl, and AH DePace. Molecular Systems Biology. (2012).
CC Fowlkes*, K Eckenrode*, MD Bragdon*, M Meyer, Z Wunderlich, L Simirenko, CL Luengo Hendriks, SVE Keränen, C Henriquez, DW Knowles, MD Biggin, MB Eisen, AH DePace. PLoS Genetics. (2011).
Z Wunderlich, LA Mirny. Different gene regulation strategies revealed by analysis of binding motifs. Trends in Genetics. (2009).
Z Wunderlich, LA Mirny. Using genome-wide measurements for computational prediction of SH2-peptide interactions. Nucleic Acids Research. (2009).
Z Wunderlich, LA Mirny. Spatial effects on the speed and reliability of protein-DNA search. Nucleic Acids Research. (2008).
W Tian, LV Zhang, M Tasan, FD Gibbons, OD King, J Park, Z Wunderlich, JM Cherry, FP Roth. Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiae gene function. Genome Biology. (2008).
G Kolesov*, Z Wunderlich*, ON Laikova, MS Gelfand, LA Mirny. How gene order is influenced by the biophysics of transcription regulation. PNAS. (2007).
A Bhattacharya, Z Wunderlich, D Monleon, R Tejero, GT Montelione. Assessing model accuracy using the Homology Modeling Automatically (HOMA) Software. Proteins: Structure, Function, Bioinformatics. (2007).
Z Wunderlich and LA Mirny. Using topology of the metabolic network to predict viability of mutant strains. Biophysical Journal. (2006).
Z Wunderlich, TB Acton, J Liu, G Kornhaber, J Everett, P Carter, N Lan, N Echols, M Gerstein, B Rost, and GT Montelione. The protein target list of the Northeast Structural Genomics Consortium. Proteins: Structure, Function, Bioinformatics. (2004).
C-S Goh, N Lan, N Echols, S Douglas, D Milburn, P Bertone, R Xiao, L-C Ma, D Zheng, Z Wunderlich, TB Acton, GT Montelione, and Mark Gerstein. SPINE 2: A system for collaborative structural proteomics within a federated database framework. Nucleic Acids Research. (2003).