My research involves the analysis of ‘omics data to understand drug response and improve drug design, for diseases like leukemia, pancreatic cancer, and depression. I’m also developing tools to simplify bioinformatics research.
Highlighted Projects
A full publication list can be found at Google Scholar.
Research with Butler Students
- Faster Assessment of Fluoxetine Response Using Transcriptomics Data. Paige Cowden, Ariel Worthington, Caleb Class. Presented at ASHP Midyear (2021).
- Identifying Early Diagnostic Features of Parkinson’s Disease Using Multi-Omics. Logan Van Ravenswaay, Katrina Retzke, Caleb Class. Presented at ASHP Midyear (2021).
Collaborative Research
- Stem cell-specific survival pathways drive the progression of myelodysplastic syndromes. Ganan-Gomez I, Yang H, Alfonso A, …, Class CA, …, Garcia-Manero G, Colla S. Nature Medicine (2022).
- Activation of Gene Expression by Protein Domains Acting as Nucleosome Detergents. Broyles BK, Gutierrez AT, Maris TP, Coil DA, Wagner TM, Wang X, Kihara D, Class CA, Erkine AM. iScience (2021).
- PRMT1-dependent regulation of RNA metabolism and DNA damage response sustains pancreatic ductal adenocarcinoma. Giuliani V, Miller MA, Liu CY, Hartono SR, Class CA, …, Heffernan TP. Nature Communications (2021).
Software Packages
- iDINGO—integrative differential network analysis in genomics with Shiny application. Class CA, Ha MJ, Baladandayuthapani V, Do KA. Bioinformatics (2018). R package available at CRAN, and Shiny application available at GitHub.
- Easy NanoString Gene Expression Analysis with the NanoTube. Class CA, Lukan CJ, Bristow CA, Do KA. Presented at Experimental Biology 2022.