We are amidst a data revolution. Just the past 5 years, the cost of sequencing a human genome has gone down approximately 10-fold. This development moves equally fast within areas such as mass spectrometry, in vitro immuno-peptide screening a.o. This facilitates the search for bio-markers, biologics, therapeutics, etc. but also redefines the requirements for storing, accessing and working with data and the skillset of bio data scientists. In this talk I will present tidysq, an R-package aiming at extending the Tidyverse framework to include (tidy) bio-data-science / bioinformatics. Tidysq will be presented in context with current status in ML driven (neo)epitope prediction within cancer immunotherapy.
Leon Eyrich Jessen
Technical University of Denmark
Tidysq for Working with Biological Sequence Data in ML Driven Epitope Prediction in Cancer Immunotherapy
We are amidst a data revolution. Just the past 5 years, the cost of sequencing a human genome has gone down approximately 10-fold. This development moves equally fast within areas such as mass spectrometry, in vitro immuno-peptide screening a.o. This facilitates the search for bio-markers, biologics, therapeutics, etc. but also redefines the requirements for storing, accessing and working with data and the skillset of bio data scientists. In this talk I will present tidysq, an R-package aiming at extending the Tidyverse framework to include (tidy) bio-data-science / bioinformatics. Tidysq will be presented in context with current status in ML driven (neo)epitope prediction within cancer immunotherapy.