Prof. Eli Eisenberg works on application of statistical methods and modeling to large-scale RNA expression data. In particular, he focuses on inconsistencies between the observed sequence-content of the RNA, as found in deep-sequencing experiments, and the reference genome. These are mostly due to technical and biological noise, but also include signatures of important regulated RNA modifications, called "RNA editing". The crucial role of these RNA modifications to the proper function of the cell and the organism has been increasingly recognized in recent decades, with A-to-I RNA editing being the most common modification. Computational approaches, such as the ones developed and employed by Eisenberg and colleagues, have become the standard tool for detection, quantification and analysis of A-to-I RNA editing events.