DBFE: distribution-based feature extraction from structural variants in whole-genome data

Maciej Piernik, Dariusz Brzezinski, Pawel Sztromwasser, Klaudia Pacewicz, Weronika Majer-Burman, Michal Gniot, Dawid Sielski, Oleksii Bryzghalov, Alicja Wozna, Pawel Zawadzki

Abstract: Whole-genome sequencing has revolutionized biosciences by providing tools for constructing complete DNA sequences of individuals. With entire genomes at hand, scientists can pinpoint DNA fragments responsible for oncogenesis and predict patient responses to cancer treatments. Machine learning plays a paramount role in this process. However, the sheer volume of whole-genome data makes it difficult to encode the characteristics of genomic variants as features for learning algorithms.