My research interests involve applying statistical reasoning to problems that bring together the fields of biology, genomics, bioinformatics, and statistics. I am especially interested in the development of statistical methodology for the analysis of high-dimensional genomic and transcriptomic data, and the implementation of such methods in open-source R/Bioconductor packages. My research is primarily focused on two objectives:
- Inferring gene regulatory networks from microarray data, particularly through the use of time-course and intervention (gene knockout and knockdown) experiments, and
- Developing sound statistical methods for the analysis of RNA-seq data, including differential expression analyses, co-expression analyses, and network inference methods.
I’m currently on a 20-month sabbatical (October 2017-May 2019) through an AgreenSkills+ fellowship to work with my colleague Dr. Paul Livermore Auer at the Zilber School of Public Health at the University of Wisconsin-Milwaukee.