Entropy Fusion DNA: Alignment-Free Gene Fusion Detection through Entropy and Mutual Information Descriptors (opens in new tab)

Gene fusions are clinically relevant genomic alterations and key cancer biomarkers. Their computational detection remains dominated by alignment-based pipelines, whose reliance on read mapping, reference annotations, and heuristic filtering makes them sensitive to mapping ambiguities, annotation incompleteness, repetitive regions, and false positives. Recent machine learning (ML) strategies aim to learn fusion-related patterns directly from sequencing data, but their adoption is still limited...