DipGNNome: Diploid de novo genome assembly with geometric deep learning and beam-search
Martin Schmitz, Lovro Vrček, Kenji Kawaguchi, Mile Šikić
DipGNNome introduces a deep learning framework for diploid genome assembly using graph neural networks and beam-search, achieving results comparable to state-of-the-art methods.