Applying Natural Language Processing to Cancer Genomics
Personalized immunotherapy is a promising treatment that can potentially deliver clinical benefit to many cancer patients. Large amounts of genetic information have to be processed to identify actionable targets for therapy.
This talk will highlight some of the ways in which natural language processing approaches can be used for the analysis of genomics data and an example of how myNEO uses NLP to bring benefit to the patient.
Principal Data Scientist at myNEO
As a principal data scientist at myNEO, Lena Pfitzer has been developing new bioinformatics solutions to advance personalized cancer immunotherapy, working on various projects like peptide immunogenicity prediction and transposable element insertion detection.
Lena studied molecular biotechnology and has been working in the cancer immunology field since her master thesis at the German Cancer Research Center, where she focused on biomarker identification for predicting the response to checkpoint inhibition therapy.