PhD, Dr. rer. nat.
Area of interest
Love’s research concerns statistical and computational methods for the analysis of high-throughput sequencing assays to facilitate biomedical and biological research. He has developed a number of open source software packages for the analysis of RNA sequencing (RNA-seq) data, including the DESeq2 package for differential gene expression analysis. In addition, he studies the effect of lab-to-lab variation on computational estimation of gene isoform abundances from RNA-seq, and has developed statistical methods for accurate estimation of isoform abundance in the presence of common technical biases. The Love Lab uses statistical models to infer biologically meaningful patterns in high-dimensional datasets, and develops open-source statistical software for the Bioconductor Project. At UNC-Chapel Hill, the lab collaborates with groups in the Genetics Department and the Lineberger Comprehensive Cancer Center, studying how genetic variants relevant to diseases are associated with changes in molecular and cellular phenotypes.
Awards and Honors
- 2017 Junior Faculty Development Award, UNC-Chapel Hill, NC