Alexander Cope, Ph.D.
Department of Genetics
Life Sciences Building, Piscataway, NJ
B.S. in Mathematics and Computer Science – Centre College, Danville, KY
Ph.D. Genome Science and Technology – University of Tennessee, Knoxville, TN
INSPIRE fellow, Department of Genetics — Rutgers University, Piscataway, NJ
Research Mentor: Premal Shah, Ph.D.
My research primarily focuses on applying models rooted in evolutionary theory to extract biological information from omics datasets. I have interests in studying the evolution and mechanisms of mRNA translation dynamics (including post-transcriptional and post-translational regulation) and the evolution of secreted proteins.
Teaching Interests: Evolutionary genetics, computational biology, bioinformatics
A.L. Cope, S. Vellappan, J.S. Favate, K.S. Skalenko, S.S. Yadavalli, P. Shah; Exploring Ribosome-Positioning on Translating Transcripts with Ribosome Profiling. In: Dassi E. (eds) Post-Transcriptional Gene Regulation. Methods in Molecular Biology, vol 2404. Humana, New York, NY, 2022, doi: https://doi.org/10.1007/978-1-0716-1851-6_5
I.A. Nikonorova, J. Wang, A.L. Cope, P. Tilton, K.M. Power, J.D. Walsh, J.S. Akella, P. Shah, M.M. Barr; Tracking extracellular vesicle (EV) cargo as a platform for studying EVomics, signaling, and targeting in vivo, bioRxiv, September 2021, doi: https://doi.org/10.1101/2021.09.23.461577 (Accepted: Current Biology)
A.L. Cope, P. Shah; Intragenomic variation in mutation biases causes underestimation of selection on synonymous codon usage, bioRxiv, November 2021, doi: https://doi.org/10.1101/2021.10.29.466462 (In Review: Plos Genetics)
Cope, A.L., Gilchrist M.A. (2021). Quantifying shifts in natural selection on codon usage between protein regions: A population genetics approach. bioRxiv. (In review: BMC Genomics)
Cope, A.L, Anderson, F., Favate, J., Jackson, M., Mok, A., Kurowska, A., MacKenzie, E., Shivakumar, V., Tilton, P., Winterbourne, S.M., Xue, S., Kavoussanakis, K., Lareau, L.F., Shah, P., Wallace, E.W.J. (2021). riboviz 2: A flexible and robust ribosome profiling data analysis and visualization workflow. bioRxiv. (Accepted: Bioinformatics, https://doi.org/10.1093/bioinformatics/btac093).
Skalenko, K.S., Li, L., Zhang, Y., Vvedenskaya, I.O., Winkelman, J.T., Cope, A.L., Taylor, D.M., Shah, P., Ebright, R.H., Kinney, J.B., Zhang, Y., Nickels, B.E. (2021). Promoter-sequence determinants and structural basis of primer-dependent transcription initiation in Escherichia coli. PNAS, 118(27), e2106388118.
Poudel, S., Cope, A.L., O’Dell, K.B., Guss, A.M, Seo, H, Trinh, C.T., Hettich, R.L. (2021). Identification and characterization of proteins of unknown function (PUFs) in Clostridium thermocellum DSM 1313 strains as potential genetic engineering targets. Biotechnology for biofuels, 14(1), 1-19.
Cope, A.L, O’Meara, B.C., Gilchrist, M.A. (2020). Gene expression of functionally-related genes coevolves across fungal species: detecting coevolution of gene expression using phylogenetic comparative methods. BMC Genomics, 21, 1-17.
Cope, A.L., Hettich, R.L., Gilchrist, M.A. (2018). Quantifying codon usage in signal peptides: Gene ecpression and amino acid usage explain apparent selection for inefficient codons. Biochimica et Biophysica Acta – Biomembranes, 1860(12), 2479-2485.
Landerer, C., Cope, A., Zaretzki, R. Gilchrist M.A. (2018). AnaCoDa: analyzing codon data with Bayesian mixture models. Bioinformatics, 34(14), 2496-2498.