Mike Domaratzki

photo of Dr Domaratzki.

Department Chair, Associate Professor

Office: Middlesex College 355
Tel: 519-661-2111 x82561
Email: mdomarat@uwo.ca

Personal Web Page Link
Social Media: @mdomarat 

Mike Domaratzki is an Associate Professor and Chair of the Department of Computer Science.  His research interests are in bioinformatics, genomics and theoretical computer science. His recent research investigates machine learning tools for genomic prediction for crops. He has taught at the graduate and undergraduate level in a variety of areas, including introductory programming, data structures and algorithms, object oriented programming, bioinformatics, and automata and formal languages.

Research Interests

Bioinformatics, Computational Genomics, Machine Learning, Theory of Computing.

Selected Publications

  1. Ajwad, M. Domaratzki, Q. Liu, N. Feizi, P. Hu, Identification of significantly mutated subnetworks in the breast cancer genome, Scientific reports, 2021
  2. C Schmidt, M Domaratzki, RP Kinnunen, J Bowman, CJ Garroway Continent-wide effects of urbanization on bird and mammal genetic diversity, Proceedings of the Royal Society B, 2020
  3. S Ravichandran, R Ragupathy, T Edwards, M Domaratzki, S Cloutier, MicroRNA-guided regulation of heat stress response in wheat, BMC Genomics, 2019
  4. S Jubair, M Domaratzki, Ensemble supervised learning for genomic selection 2019 IEEE International Conference on Bioinformatics and Biomedicine.
  5. A Hogan et al., Competitive fitness of essential gene knockdowns reveals a broad-spectrum antibacterial inhibitor of the cell division protein FtsZ, Antimicrobial agents and chemotherapy, 2018.
  6. A Gislason, K Turner, M Domaratzki, S Cardona, Comparative analysis of the Burkholderia cenocepacia K56-2 essential genome reveals cell envelope functions that are uniquely required for survival in species of the genus Burkholderia, Microbial Genomics, 2017
  7. R Ragupathy, S Ravichandran, Md Mahdi, D Huang, E  Reimer, M Domaratzki, S Cloutier, Deep sequencing of wheat sRNA transcriptome reveals distinct temporal expression pattern of miRNAs in response to heat, light and UV, Scientific reports, 2016