About
Chad Myers is a computational biologist whose research focuses on machine learning approaches for integrating diverse genomic data, with the aim of making inferences about biological networks.
The main purpose of his work is to further the understanding of gene function and how genes or proteins interact to carry out cellular processes.
Awards
- University of Minnesota George W. Taylor Career Development Award, 2013
- University of Minnesota McKnight Land-Grant Professorship, 2011–2013
- NSF CAREER Award, 2010
Relevant Publications
Deshpande, R. et al. “A comparative genomic approach for identifying synthetic lethal interactions in human cancer.” Cancer Res. 73, no. 20 (October 2013): 6128–6136.
Stessman, H.A. et al. “Profiling bortezomib resistance and identification of secondary therapies in a mouse myeloma model.” Mol Cancer Ther. 12, no. 6 (June 2013): 1140–1150.
Koch, E. et al. “Conserved rules govern genetic interaction degree across species.” Genome Biol. 13, no. 7 (2012): R57.
Swanson-Wagner, R. et al. “Reshaping of the maize transcriptome by domestication.” PNAS 109, no. 29 (July 2012): 11878–11883.
Costanzo, M. et al. “The genetic landscape of a cell.” Science 327, no. 5964 (January 2010): 425–31.