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Prof. Eli Eisenberg’s laboratory specializes in applying advanced algorithmic and statistical methods and modeling to analyze large-scale RNA expression data.
Key capabilities include:
> Detection and Quantification of RNA Editing: Pioneering computational approaches for detecting and quantifying A-to-I RNA editing events across various RNA classes, including repetitive elements, coding sequences, and micro-RNAs. These methods are based on analysis of inconsistencies between observed DNA and RNA sequence-content from deep-sequencing experiments and the reference genome, addressing technical and biological noise.
> Characterization of RNA Editing: Comprehensive analysis of RNA editing regulation, accurate quantification of differential editing, highlighting their crucial role in cellular function and organismal health.
Applications
The lab’s research finds applications in:
> Biomedical Research: Studying RNA editing in normal and cancerous tissues, revealing global deregulation patterns in tumors and their implications for disease mechanisms.
> Comparative Genomics: Comparative analysis across species, such as cephalopods, demonstrating exceptionally high levels of recoding and its evolutionary significance.
Potential Markets
Our work has potential impacts in:
> Pharmaceuticals and Therapeutics: Targeting RNA editing mechanisms for potential therapeutic interventions in cancer and other diseases.
> Genomics and Precision Medicine: Enhancing understanding of RNA modifications for personalized medicine approaches and biomarker discovery.
> Off-target editing by engineered deaminases: Tools developed for the study of endogenous RNA editing are highly effective in quantifying DNA and RNA off-target editing in the context of programmed site-directed RNA editing.
RNA Editing Indexer Tool: https://github.com/a2iEditing/RNAEditingIndexer
Key Publications:
> https://www.nature.com/articles/s41576-018-0006-1
