Regulatory DNA encodes the gene regulatory networks that are required for virtually every process in an a nimal, 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.
Graduate students must be part of one of BU's graduate programs, e.g. the Molecular Biology, Cell Biology & Biochemistry program or the Biology program. The Wunderlich lab is actively recruiting rotation students for the 2021-2022 academic year. Please email Zeba if you are interested.
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 studies of gene regulation should contact Zeba to discuss possible projects.
PhD, Harvard University, Biophysics
BA, Molecular Biology & Biochemistry, Statistics, Rutgers University
BS, Genetics, UC Davis
BS, Neuroscience, College of William & Mary
BS, Biology, BA Chemistry, Florida International University
PhD, Biology, UCSD
BS, Biological Sciences, Carnegie Mellon University
BS, MS, Perdue University
PhD Student, 2015-2021
Undergraduate Student, 2019-2021, now a PhD student at USC
Junior Specialist, 2020-2021, now a Master's student at CSU Long Beach
Undergraduate Student, 2020-2021
Undergraduate Student, 2020-2021
Undergraduate Student, 2020-2021, now a MPH student at UCLA
Research Assistant, 2019-2020
Junior Specialist, 2019-2020, now at UCSF School of Dentistry
High School Student, Summer 2019, now an undergraduate at Emory University
Undergraduate Student, Public Health Sciences, 2017-2019, now at Thermo Fisher Scientific
Research Assistant, 2017-2018, now at Western University of Health Sciences
Undergraduate Student, Biomedical Engineering, 2016-2017, now in UCI MD/PhD program
Undergraduate Student, Genetics and Anthropology, 2015-2016, now at the Vincent J Coates Genomics Sequencing Lab at UC Berkeley
Masters Student, Biotechnology Management, 2016-2017, now at BD Biosciences
Masters Student, Developmental and Cell Biology, 2015-2017
For an up-to-date and complete list of publications, see Google Scholar.
F Lopez-Rivera, OK Foster, BJ Vincent, ECG Pym, MDJ Bragdon, J Estrada, AH DePace, Z Wunderlich. G3. (2020).
Selected older works:
Z Wunderlich, MD Bragdon, K Eckenrode, T Martin, S Pearl, and AH DePace. Dissecting sources of quantitative gene expression pattern divergence between Drosophila species. Molecular Systems Biology. (2012).
Z Wunderlich, AH DePace. Modeling transcriptional networks in Drosophila development at multiple scales. Current Opinion in Genetics and Development. (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).
G Kolesov*, Z Wunderlich*, ON Laikova, MS Gelfand, LA Mirny. How gene order is influenced by the biophysics of transcription regulation. PNAS. (2007).
Z Wunderlich and LA Mirny. Using topology of the metabolic network to predict viability of mutant strains. Biophysical Journal. (2006).